Interactive adjustable seat with multiple operating modes

Abstract

A system and method for automatic seat adjustment, the system and method including a seat frame, a plurality of seat cushions coupled to the seat frame, a plurality of adjustable bladders housed within the plurality of seat cushions, and a plurality of sensors housed within the plurality of seat cushions. The system and method also includes a memory for storing user data and a plurality of seat adjustment programs for controlling at least one of the plurality of adjustable bladders. The system and method further includes at least one controller coupled to the memory, the plurality of adjustable bladders, and the plurality of sensors, the at least one controller configured to alter at least one of the plurality of adjustable bladders based on feedback from at least one of the plurality of sensors, the user data, and the seat adjustment program.

Description

Background Art

[0001]

[0001] The seats of automobiles and similar vehicles have evolved over time. The seats have been improved in terms of passenger safety, comfort, and convenience. Conventionally, a seat includes a frame for attaching the seat to a vehicle and has a pad and a seat cover. More recently, electric adjustable position adjustment, lumbar support, and heating and cooling have been incorporated into vehicle seats. However, most seat solutions are designed generically to be applicable to a variety of different passengers.

Summary of the Invention

Problems to be Solved by the Invention

[0002]

[0002] Currently available seats may include features that provide a limited number of comfort functions, but the comfort functions are often implemented as stand-alone features and rely on manual input from the passenger. This approach to comfort results in limited options that may be difficult to navigate. In addition, this approach does not take into account that future vehicle drivers will spend less time driving the vehicle (due to semi-autonomous and autonomous vehicle technologies) and may desire more comfort, convenience, and physical and emotional benefits from the vehicle seat.

Means for Solving the Problems

[0003]

[0003] In one embodiment, a system for automatic seat adjustment is provided. This system includes a seat frame, a plurality of seat cushions coupled to the seat frame, a plurality of adjustable bladders housed within the plurality of seat cushions, and a plurality of sensors housed within the plurality of seat cushions. This system also includes a memory for storing user data and a plurality of seat adjustment programs for controlling at least one of the plurality of adjustable bladders. This system further includes at least one controller coupled to the memory, the plurality of adjustable bladders, and the plurality of sensors, the at least one controller being configured to modify at least one of the plurality of adjustable bladders based on feedback from at least one of the plurality of sensors, user data, and a seat adjustment program.

[0004]

[0004] In some embodiments, the seat cushions include a seat base, a backrest, and a headrest. The system may further include a plurality of temperature control devices. The system may further include a plurality of audio output devices. The system may further include a plurality of haptic feedback generators. The plurality of sensors may include a combination of physiological sensors, pressure sensors, and temperature sensors.

[0005]

[0005] In another embodiment, a method for automatic seat adjustment is provided.

[0006] The accompanying drawings, where similar reference numerals refer to identical or functionally similar elements across separate figures, are incorporated herein, together with the following detailed description, form part of the specification, further illustrate embodiments, and help illustrate the various principles and advantages of those embodiments. [Brief explanation of the drawing]

[0006] [Figure 1]

[0007] This is a block diagram of a system according to several embodiments. [Figure 2]

[0008] This figure schematically illustrates a set of subsystems included in the system of Figure 1 according to several embodiments. [Figure 3A]

[0009] This is a diagram of a seat according to several embodiments. [Figure 3B] This is a diagram of a seat according to several embodiments. [Figure 3C] This is a diagram of a seat according to several embodiments. [Figure 3D] This is a diagram of a seat according to several embodiments. [Figure 3E] This is a diagram of a seat according to several embodiments. [Figure 3F] This is a diagram of a seat according to several embodiments. [Figure 3G] This is a diagram of a seat according to several embodiments. [Figure 4A]

[0010] This is a flowchart of methods for implementing static comfort according to several embodiments. [Figure 4B]

[0011] This figure illustrates various embodiments of pressure measurement evaluated by the method shown in Figure 4A. [Figure 4C] This figure illustrates various embodiments of pressure measurement evaluated by the method shown in Figure 4A. [Figure 5A]

[0012] This is a flowchart of a method for implementing dynamic comfort according to several embodiments. [Figure 5B] This is a flowchart of a method for implementing dynamic comfort according to several embodiments. [Figure 6]

[0013] This is a flowchart of a method for performing biometric massage according to several embodiments. [Figure 7]

[0014] This is a flowchart of methods for heart rate variability (HRV) and stress analysis according to several embodiments. [Figure 8]

[0015] A flowchart of a method for performing a music massage according to some embodiments. [Figure 9]

[0016] A flowchart of a method for performing a game (e.g., Simon Says) according to some embodiments. [Figure 10]

[0017] A flowchart of a method for performing a dance simulator according to some embodiments. [Figure 11]

[0018] A flowchart of a method for performing a yoga session according to some embodiments. [Figure 12]

[0019] A diagram of a heating and cooling method for use according to the method of FIGS. 8 to 11 according to some embodiments.

Embodiments for Carrying Out the Invention

[0007]

[0020] Those skilled in the art will recognize that the elements in the figures are illustrated for simplicity and clarity and are not necessarily drawn to scale. For example, the dimensions of some elements in the figures may be exaggerated relative to other elements to enhance understanding of the embodiments of the present disclosure.

[0008]

[0021] The components of the apparatus and method are represented in the drawings, where appropriate, by conventional symbols and are illustrated only with specific details important in understanding the embodiments of the present disclosure so as not to obscure the disclosure with details that would be readily understood by those skilled in the art having the advantages of the description herein.

[0009]

[0022] The present disclosure provides a seat comfort system that senses various physical and physiological metrics of a seat occupant to detect and address the occupant's comfort and emotional state. Comfort and emotional state can be improved by adjusting a number of integrated support, contour, heating / ventilation, and other treatment systems. Methods for improving occupant comfort and treatment include static comfort adjustment, dynamic comfort adjustment, vibration massage, biometric massage, music-driven massage, interactive seat games, and heating and cooling. In implementing these methods, the present disclosure adjusts different physical components of the seat to match the occupant's unique size, shape, and needs, and implements a series of comfort features to improve occupant comfort, support, and well-being. Embodiments can, among other things, adjust a number of seat components including seat cushions, firmness, positioning, ventilation, and massage bladders to promote the specific physical and mental health of the seat occupant. The system also uses a number of pressure sensors to provide feedback to the controller regarding the occupant's physical characteristics and dynamic interaction with the seat. Such adjustment and treatment options can be dynamically changed to address the transient nature of health and comfort by continuously monitoring a selected set of parameters and reacting accordingly.

[0010]

[0023] The systems and methods of this disclosure offer numerous advantages over conventional seats. These advantages include ease of use requiring minimal input from the occupant, a personalized experience based on individual occupant measurement data (pressure, temperature, posture, etc.), optimized adjustments to ensure continuous comfort throughout the entire driving experience, and accurate health coring based on seat measurements and / or artificial intelligence. Direct assessment of the occupant's emotional and physiological state influences the adjustments made to the seat. Certain embodiments improve the overall in-vehicle experience and entertainment by individually addressing the needs of the driver and passenger, and also improve the overall interaction between the occupant and the seat surface. In some cases, a passenger seat user may benefit from various modes that are not available to the driver. For example, seat environments can be adjusted to suit activities such as conversation mode, reading mode, or sleep mode, and modes such as games, yoga, and other entertainment activities may be offered only to passengers in autonomous / autonomous vehicles. In contrast, fatigue reduction therapy may be more suitable for drivers of standard vehicles.

[0011]

[0024] Before the embodiments are described in detail, it should be understood that the application of the embodiments is not limited to the details of the configuration and arrangement of components described in the following description or illustrated in the following drawings. Other embodiments are possible, and the described embodiments can be practiced or executed in various ways. For example, the systems herein show components logically separately, but it should be understood that such depictions are for illustrative purposes only. In some embodiments, the illustrated components may be combined or separated into separate software, firmware, and / or hardware. These components may run on the same computing device or be distributed across different computing devices connected by one or more networks or other suitable communication connections.

[0012]

[0025] For the sake of clarity, some or all of the exemplary systems presented herein are illustrated by a single sample of each of their component parts. Some examples may not describe or illustrate all of the components of the system. Other exemplary embodiments may have more or fewer of each of the illustrated components, and may combine some components or include additional or alternative components.

[0013]

[0026] Furthermore, while certain drawings illustrate hardware and software located within a particular device, it should be understood that these depictions are for illustrative purposes only. In some embodiments, the illustrated components may be combined or separated into separate software, firmware, and / or hardware. For example, logic and processing may be distributed across multiple electronic processors rather than being located and executed within a single electronic processor. Regardless of how they are combined or separated, hardware and software components may be located on the same computing device or distributed across different computing devices connected by one or more networks or other appropriate communication links.

[0014]

[0027] Figure 1 illustrates an exemplary system 100 for automatically assessing and controlling one or more parameters of a seat 102 and a user 104 (e.g., a vehicle occupant) sitting in the seat 102. The system 100 implements a combination of devices that assess the health status of the user 104 and adjust the seat 102 to improve the user's health status. Health status may include a combination of the user 104's physical, emotional, and mental attributes. In some embodiments, the system 100 includes a seat 102, a computing environment 106 communicatively coupled to a storage system 108, a plurality of feedback devices 110, at least one display device 112, and optionally one or more user devices 114. The computing environment 106 includes a computing device having an electronic processor 120, memory 122, input / output interface 124, and an operating system configured to perform operations for applications installed therein (e.g., in memory 122). As shown in Figure 1, the computing environment 106 may include, for example, a programmable logic controller (PLC), a microcontroller unit (MCU), a computer, a server, a laptop, a handheld device, or other computing devices. In some embodiments, the computing environment 106 is part of the vehicle's computing architecture. For example, the computing environment may be part of an infotainment system in a vehicle.

[0015]

[0028] Although the computing environment 106 is described for illustrative purposes as a single entity having a single processor 120, embodiments may utilize different numbers of computing devices and processors in many different ways. For example, the computing environment 106 may include a single computing device, a collection of computing devices in a network computing system, a cloud computing infrastructure, or a combination thereof. Thus, embodiments of the present disclosure are not limited to a single computing environment 106, nor are they limited to a single type of implementation or configuration of the exemplary computing environment 106. The computing environment 106 is merely an exemplary example of a suitable computing system.

[0016]

[0029] As shown by returning to Figure 1, the various components contained within the computing environment 106, along with various other modules and components (not shown), are coupled to one another by or through one or more connections (e.g., control buses or data buses) that enable communication between the components. The use of control buses and data buses for interconnection and information exchange between the various modules and components will be apparent to those skilled in the art, given the description provided herein.

[0017]

[0030] The processor 120 processes information by, for example, retrieving and providing information from memory 122 via a communication interface and executing software instructions or programs. Memory 122 may include program storage and data storage areas and may include random access memory ("RAM"), read-only memory ("ROM"), or other non-temporary computer-readable media within memory 122. In some embodiments, memory 122 stores data related to seat 102 and user 104, among other things, as will be discussed in more detail herein. Program storage may include firmware, one or more executable applications, program data, filters, rules, one or more program modules, and other executable instructions. The processor 120 is configured to retrieve information from memory 122 and execute programs or applications related to the methods described herein, among other things.

[0018]

[0031] As illustrated in Figure 1, the computing environment 106 may include a storage system 108 or be communicatively coupled to the storage system 108. Similar to memory 122, the processor 120 retrieves and provides information from the storage system 108, for example, via a communication interface. The storage system 108 may include a combination of devices configured to store and organize collections of data. For example, the storage system 108 could be a local storage device within the computing environment 106, a remote database function, or a cloud computing storage environment accessible via a network 116 (e.g., a Controller Area Network (CAN) or other vehicle network). The storage system 108 may also include a database management system that utilizes a database model. The database management system may be configured, for example, to interact with users through queries and facilitate the analysis of data in the database.

[0019]

[0032] In some embodiments, using data and programming provided in combination with memory 122 and storage system 108, the computing environment 106 performs various aspects of the disclosure using machine learning. Machine learning generally refers to the ability of a computer program to learn without being explicitly programmed. In some embodiments, the computer program (often referred to as the learning engine) is configured to build a model (e.g., one or more algorithms) based on exemplary inputs. Supervised learning involves presenting the computer program with exemplary inputs and their desired (actual) outputs. The computer program is configured to learn general rules (models) that map inputs to outputs of training data. Machine learning can be performed using various types of methods and mechanisms. Exemplary methods and mechanisms include decision tree learning, association rule learning, artificial neural networks, inductive logic programming, support vector machines, clustering, Bayesian networks, reinforcement learning, representation learning, similarity and metric learning, sparse dictionary learning, and genetic algorithms. Using some or all of these approaches, a computer program may take in, analyze, understand, and incrementally refine a model of data analysis, including image analysis. Once trained, computer systems can be referred to as intelligent systems, artificial intelligence (AI) systems, deep learning systems, cognitive systems, and so on.

[0020]

[0033] In some embodiments, data is input by user 104 or acquired from various sources for use by computing environment 106. For example, computing environment 106 may receive data from a combination of sources including, for example, a storage system 108, a feedback device 110, and a user device 114. In some embodiments, storage system 108 includes historical data, collected data about user 104, and a combination of algorithms / programming for analyzing the data.

[0021]

[0034] In some embodiments, the feedback device 110 includes a combination of a data acquisition device that obtains information about the user 104 and a data output device for communicating information to the user 104. For example, the feedback device 110 may include a camera, physiological sensors, biometric sensors, pressure sensors, and wearable devices. The feedback device may also include audio, video, and haptic devices. In some embodiments, the user device 114 is a device operated by the user 104. For example, the user device 114 may include a smartphone, laptop, wearable device, smartwatch, fitness tracker, etc., which can be paired or communicatively coupled with the computing environment 106 for data sharing.

[0022]

[0035] Each of the seats 102, computing environment 106, storage system 108, multiple feedback devices 110, and one or more user devices 114 are communicatively coupled to one another. Communicative coupling can be provided via any combination of direct (e.g., wired) or indirect (e.g., via network 116) connections to the computing environment 106. Network 116 may be implemented using a combination of wired or wireless communication components and connections. Network 116 may be used to exchange data between the computing environment 106, feedback devices 110, and user devices 114, to exchange data with the storage system 108, and / or to collect or share data with additional sources (e.g., external databases). In some embodiments, devices may use network 116 to establish connections to other networks, such as cellular networks and / or the Internet. In addition, components such as the storage system 108 may be located remotely (e.g., in the cloud) and communicate with the components via network 116 or another connection.

[0023]

[0036] Each device in system 100 may include a communication interface for communicating over network 116. The communication interface is configured to receive inputs and provide system outputs. The communication interface receives information and signals from both internal and external devices of the computing environment 106 (for example, via one or more wired and / or wireless connections) and provides information and signals to those devices. The communication interface may include a wireless transmitter or transceiver for wireless communication over network 116. Alternatively, in addition to a wireless transmitter or transceiver, the communication interface may include wired connections.

[0024]

[0037] Continuing the description of Figure 1, in some embodiments, the computing environment 106 includes or is communicatively coupled to a display device 112, such as a liquid crystal display (LCD) touchscreen or an organic light-emitting diode (OLED) touchscreen. In some embodiments, the computing environment 106 implements a graphical user interface (GUI) (for example, generated by a processor 120 from instructions and data stored in memory 122 and presented on the display 112) to allow a user to interact with the computing environment 106. For example, a vehicle including seats 102 may include a display 112 (for example, an infotainment system, a human-machine interface (HMI), etc.). In some embodiments, the computing environment 106 allows data to be displayed remotely using a display (configured similarly to the display 122) on a user device 114, for example. As previously discussed, a combination of connections can be used to provide data from the computing environment 106 to a local or remote display 112.

[0025]

[0038] In some embodiments, the computing environment 106 includes a combination of dedicated modules configured to perform various functions of the present disclosure (in one example, a program or group of programs, which are illustrated separately but may even be stored in memory 122 or storage system 108). In some embodiments, the computing environment 106 includes a static comfort module 130, a dynamic comfort module 132, a massage module 134, a temperature module 136, and an interaction module 138 (often referred to as the seat adjustment program). The combination of modules, combined with other embodiments of system 100, is used to monitor the parameters and characteristics of user 104 and seat 102. In some cases, the modules analyze data and provide feedback to user 104 and / or commands or control signals to components of seat 102 or other vehicle components.

[0026]

[0039] In some embodiments, the static comfort module 130 is configured to evaluate and establish the contour of the seat based on an automated initial assessment of the user 104 and / or manual input provided by the user 104. In some embodiments, the dynamic comfort module 132 is configured to continuously monitor the comfort, health, and emotional state of the seat user 104 and provide adjustments to the seat 102 accordingly. In some embodiments, the massage module 134 is configured to monitor biometric signals from the user 104 sitting in the seat 102 and to suggest or perform treatments for the user 104 using haptic feedback. In some embodiments, the temperature module 136 is configured to provide heating and cooling to the user 104 via the seat 102 depending on various factors. In some embodiments, the interaction module 138 is configured to enhance the interaction between the seat 102 and the user 104 for health and wellness, entertainment, and / or exercise purposes. As will be recognized by those skilled in the art, the static comfort module 130, the dynamic comfort module 132, the massage module 134, the temperature module 136, and the interaction module 138 may include combinations of hardware and software configured to perform various aspects of the present disclosure. Each module may be configured to provide a system to a user, individually or in combination, depending on the desired operation of the seat 102 or the requirements of the user 104.

[0027]

[0040] As shown with reference to Figure 2, in some embodiments, the module is combined with a combination of mechanical and electrical subsystems to provide physical feedback to the seat 102 and the user 104. The mechanical and electrical subsystems may include a combination of mechanisms for adjusting the seat 102 itself or the area around the user 104 inside the seat 102. In some embodiments, the seat 102 includes a seat adjustment subsystem 230, a physiological sensor subsystem 232, a haptic feedback subsystem 234, a temperature subsystem 236, and an audio / visual (A / V) feedback subsystem 238. Each subsystem, and each component, may be controlled by one or more of modules 130, 132, 134, 136, and 138. The subsystems provided in Figure 2 may include a combination of mechanical, electrical, and pneumatic mechanisms. Depending on the type of mechanism used, the seat 102 may include at least one pump, valve, motor, etc.

[0028]

[0041] In some embodiments, the seat 102 includes a combination of power and communication media that provides control over various seat subsystems and associated mechanisms. For example, the communication media may include cabling, conductive wiring, fiber optic connections, wireless connections, etc. The power and communication media can be selected based on the type of mechanism and preferred technology, cost, etc. In some embodiments, the seat 102 may include at least one system for controlling various components and subsystems of the seat 102. The electronics may include the computing environment 106 discussed with respect to Figure 1, or may include a separate combination of hardware and software configured to communicate with system 100.

[0029]

[0042] As shown with reference to Figure 3A, in some embodiments, the seat 102 includes a combination of elements conventionally found in seats, as well as modules and / or subsystems discussed with respect to Figures 1 and 2. The seat 102 is designed to include a frame 300 for mounting the seat 102 to, for example, a vehicle. The frame 300 includes a base frame portion 302 and a backrest frame portion 304 for receiving components related to the seat base 306 and backrest 308, respectively. The backrest frame portion 304 also includes a mount for the headrest 310. The seat base 306, backrest 308, and headrest 310 typically include a contoured pad (e.g., foam) wrapped in a seat cover, such as cloth or leather. In some embodiments, the seat 102 includes multiple bolster pairs 306a, 308a (e.g., base cushion bolster 306a and backrest cushion bolster 306b) on the sides of the seat cushion to further fit the user 104 to the seat 102. Similarly, the backrest 308 includes shoulder support and lumbar support. The seat cushion of the seat base 306 and backrest 308 may include a surface A and a surface B, a central portion, and two bolster regions. Each bolster region is adjacent to the central portion of the seat cushion. The upper surface of the seat cushion (closest to the occupant) may be referred to as surface A, and the lower surface (closest to the frame 300) may be referred to as surface B.

[0030]

[0043] In some embodiments, the seat 102 also includes a seat adjustment subsystem 230 which includes a combination of mechanical structures for adjusting the position, orientation, contour, stiffness, and other characteristics of the seat 102. The seat adjustment subsystem 230 provides a mechanism for adjusting the level of support and comfort of the user 104 by changing the contour and pressure levels of different areas of the seat 102. For example, the seat 102 includes a mechanism for adjusting the forward and backward movement of the seat, the seat height, the recline angle of the seat back 308, the angle of the seat base 306, the adjustment of the headrest 310, and so on. In some embodiments, the seat 102 includes a combination of electromechanical elements for adjusting other aspects of the seat 102. For example, the seat 102 may include mechanisms such as lumbar support adjustment, seat heating, cooling / ventilation, bolster adjustment, shoulder adjustment, headrest adjustment, and an airbag module. In addition, the seat 102 includes a combination of cables, switches, and motors or actuators for manually or automatically controlling the elements of the seat 102. For example, the recline angle of seat 102 may include either a mechanical lever that unlocks the recline feature, allowing the user to manually recline the seat back 308, or a switch that activates a motor that moves the seat back 308.

[0031]

[0044] As shown with reference to Figure 3B, in some embodiments, the seat adjustment subsystem 230 includes a combination of components for controlling the contouring of the seat 102 and adjusting the level of comfort for the user 104 sitting in the seat 102. User 104's comfort can be controlled by changing at least one of the following: the contouring, position, stiffness, etc. of the seat 102. For example, the seat adjustment subsystem 230 includes controls for adjusting the base frame 302 and seat base 306, the backrest frame 304 and backrest 308, and the headrest 310. The controls can be operated by the user 104 to change the entire seat 102 or a part of the seat. For example, the user 104 can adjust the recline angle of the backrest or change the lumbar support of the backrest, the bolsters 306a, 308a, the suspension, stiffness, etc.

[0032]

[0045] In some embodiments, the seat 102 includes multiple fluid-filled bladders 312 distributed throughout the seat 102. The multiple bladders 312 can be located in various places within the seat 102, providing targeted control over the comfort of the user 104 when seated in the seat 102. For example, the multiple bladders 312 can be located on the seat base 306, the backrest 308, and the A-plane of the cushion, including the bolsters 306a, 308a. Any number of multiple bladders 312 can be used, and the more bladders there are, the greater the granularity or control in customizing the comfort of the occupant of the seat 102. For example, as depicted in Figure 3B, there are 20 bladders 312 on the seat base 306, 20 bladders on the backrest 308, and four more bladders on the shoulder support of the backrest 308.

[0033]

[0046] In some embodiments, the contour and / or stiffness of the seat 102 is modified using multiple bladder 312. Fluid can be added to or removed from each of the multiple bladder 312 to modify the contouring and / or stiffness of the seat 102. To add stiffness to a particular area of ​​the seat 102, fluid is injected into one or more bladder 213 at that location. Similarly, to soften a particular area of ​​the seat 102, fluid is removed from one or more bladder 213 at that location. By inflating specific bladders, the seat contouring can be provided to accommodate different body types, sizes, etc., and different bladder 312 are selected for inflation / deflation based on the various characteristics of the occupant of the seat 102. The bladder can be adjusted alone or in combination with other components of the seat 102 (e.g., bolster, cushion support structure, headrest, lumbar support, etc.) to properly fit the occupant and simultaneously optimize the comfort and support of the user 104, as will be discussed in more detail with respect to Figures 4-5B.

[0034]

[0047] As shown with reference to Figure 3G, in some embodiments, the multiple bladders 312 include, or communicate with, multiple pressure sensors 324 to measure the fluid pressure within each of the multiple bladders 312, the pressure applied to the user 104 by the multiple bladders 312, and / or the pressure applied to the multiple bladders 312 by the user 104. The multiple pressure sensors 324 can include any combination of pressure sensors 324. For example, the multiple pressure sensors 324 can include an array of inline pressure sensors incorporated into each of the multiple bladders 312, and / or interface pressure sensors inserted in, on, and / or under the cushions. Using different pressure sensors in combination can improve accuracy, reliability, etc. For example, inline pressure sensors can be used individually or simultaneously with interface pressure sensors. In some embodiments, the multiple pressure sensors 324 are incorporated into the multiple bladders 312. The pressure sensor 324 can be provided within each of the multiple bladders 312, or in association with each of the multiple bladders 312 in other ways, or in a selected bladder 312. Different types of pressure sensors 324 can be placed in different locations within the seat 102. For example, an interface pressure sensor 324 can be applied between the bladder 312 and the cushion.

[0035]

[0048] As shown with reference to Figure 3C, in some embodiments, the seat 102 includes a haptic feedback subsystem 234. The haptic feedback subsystem 234 includes a combination of mechanisms for providing physical feedback to the user 104, such as tactile feedback and kinesthetic feedback. Tactile feedback addresses tactile perception, such as vibration. Kinesthetic feedback addresses kinesthetic perception of the action of one's own muscles. In some embodiments, the haptic feedback subsystem 234 includes a plurality of massage bladders 314, which are integrated within a plurality of bladders 312 or otherwise associated with a plurality of bladders 312. The massage bladders 314 may be positioned on the A-side and / or B-side of the seat cushion. For example, the massage bladder 314 may be positioned on the A-side and the plurality of bladders 312. The massage bladder 314 and the plurality of bladders 312 may be specifically positioned and located around the seat 102 to provide a particular function. For example, a massage bladder 314 can be placed on side A of the seat cushion to provide massage feedback to the user, while multiple bladder 312 placed on side B of the seat cushion can be provided to form the overall contour of the seat.

[0036]

[0049] Multiple massage bladders 314 can be used in combination with multiple bladders 312. The number of massage bladders 314 may be in a one-to-one relationship with each of the multiple bladders 312, and may be less than or more than the number of multiple bladders 312. For example, as depicted in Figure 3C, the seat 102 may include four A-side shoulder massage bladders 314, 20 A-side back massage bladders 314, and 20 A-side base cushion massage bladders 312. The massage bladders 314 are configured to operate in various patterns to provide therapeutic benefits to the user 104 and to provide treatment according to one or more monitored attributes of the user 104, as will be discussed in more detail with respect to Figures 5A to 12.

[0037]

[0050] As shown with reference to Figure 3D, in some embodiments, the haptic feedback subsystem 234 includes a plurality of tactile feedback devices 316 for generating vibrations that act on the user 104. The feedback devices 316 may include combinations of devices that generate tactile outputs. For example, the tactile feedback devices 316 may include massage bladder 314, haptic motors, rollers, actuators, etc. The feedback devices 316 may be individual devices located in different places within the seat 102. For example, the feedback devices 316 may be embedded in cushioning material (e.g., between sides A and / or B of the seat cushion), on side A of the cushion, or on side B of the cushion. A large number of feedback devices 316 can be used in various locations within the seat 102. The number of feedback devices 316 may be in one-to-one combinations with each of the plurality of bladders 312, a number less than the number of bladders 312, or a number greater than the number of bladders 312. The number of feedback devices 316 can be adjusted (increased / decreased) depending on the seat design and application. For example, as depicted in Figure 3D, the seat 102 may include eight feedback devices 316, four of which are located on the backrest 308 and two on the seat base 306. The feedback devices 316 are configured to operate in various patterns to provide therapeutic and recreational benefits to the user 104 and to provide treatment and entertainment according to one or more monitored attributes of the user 104, as will be discussed in more detail with respect to Figures 5A to 12.

[0038]

[0051] Continuing the description of Figure 3D, in some embodiments, the seat 102 includes an A / V feedback subsystem 238. The A / V feedback subsystem 238 includes a combination of mechanisms for providing audio and / or visual feedback to the user 104. The audio and / or visual feedback includes mechanical and electrical components that provide audio or visual cues to the user 104. In some embodiments, the A / V feedback subsystem 238 includes a plurality of haptic feedback devices 318 and a display device such as a display device 112 or a user device 114. In some embodiments, the A / V feedback subsystem 238 is configured to work in conjunction with existing audio and visual output devices located around the seat 102. For example, if the seat 102 is located in a vehicle, the A / V feedback subsystem 238 can be communicatively coupled to the vehicle's speaker system, an in-vehicle infotainment or HMI display (or other display) housing the seat 102, and / or a user device 114 in the vehicle.

[0039]

[0052] In some embodiments, as illustrated in Figure 3D, the seat 102 includes a plurality of haptic feedback devices 318 for generating haptic feedback to the user 104. For example, the haptic feedback devices 318 may be voice coils, linear actuators, rollers, etc. The haptic feedback devices 318 may be individual devices located in different places within the seat 102. For example, the haptic feedback devices 318 may be located under the cushion (e.g., on side B), embedded in the cushion, or on top of the cushion (e.g., on the headrest 110). The haptic feedback devices 318 may be associated with each of the plurality of bladders 312 on a one-to-one basis, or with fewer or more than the number of bladders 312. For example, as depicted in Figure 3D, the seat 102 includes four haptic feedback devices 318 located on the backrest 308 near the lumbar support. The haptic feedback devices 318 may also include devices outside the seat 102, such as speakers in the vehicle, on the user device 114. The haptic feedback device 318 is configured to operate in various patterns to provide therapeutic and entertainment benefits to the user 104 and to provide treatment and entertainment according to one or more monitored attributes of the user 104, as will be discussed in more detail with respect to Figures 5A to 12.

[0040]

[0053] As shown with reference to Figure 3E, in some embodiments, the seat 102 includes a temperature subsystem 236. The temperature subsystem 236 includes a combination of mechanisms for providing heating and / or cooling to the user 104. Heating and cooling are provided by mechanical and electrical components. In some embodiments, the temperature subsystem 236 includes a plurality of temperature control elements 320 for providing a target temperature change to an area on the seat 102. The plurality of temperature control elements 320 are located in various places throughout the seat 102, for example, on the backrest 308 and the seat base 306. In some embodiments, the plurality of temperature control elements 320 are also located on the bolsters 306a, 308a, and optionally on or within the headrest 310.

[0041]

[0054] In some embodiments, the multiple temperature control elements 320 are heating pads for providing localized heating to improve comfort and / or enhance individual functions implemented in the seat (e.g., therapeutic massage) and / or optimize the user experience. The heating pads can be used to provide targeted heating based on individual preferences and / or therapeutic effects. In some embodiments, the multiple heating pads can be individually controlled to provide different levels of heating at different locations on the seat 102. For example, the multiple heating pads may have different heat levels based on areas that may be associated with different temperature sensitivities or user preferences. The multiple temperature control elements 320 are not limited to heating pads and may include combinations of devices capable of generating heat. For example, the multiple temperature control elements 320 may include heating coils, heating vents, or systems for heating fluids within multiple bladder 312.

[0042]

[0055] In some embodiments, the multiple temperature control elements 320 are cooling vents or pads for providing localized cooling. Cooling vents can be used to provide targeted cooling based on personal preference, game, massage pattern, therapeutic effect, etc. In some embodiments, the cooling vents are individually controlled to provide different levels of cooling at different locations on the seat 102. For example, multiple cooling vents may have different cooling levels based on areas that may be associated with different temperature sensitivities or user preferences. In some cases, the multiple temperature control elements 320 include a cooling gel or a system for cooling fluids within multiple bladder 312.

[0043]

[0056] As shown with reference to Figure 3F, in some embodiments, the temperature subsystem 236 includes a plurality of temperature sensing elements 322 for monitoring the temperature at different locations on the seat 102. The plurality of temperature sensing elements 322 are located across the seat 102, for example, on the backrest 308 and the seat base 306. In some embodiments, the plurality of temperature sensing elements 322 are also implemented using the bolsters 306a, 308a, and optionally the headrest 310. The plurality of temperature sensing elements 322 can be located near each of the temperature control elements 320 or at different locations on the seat 102. In some embodiments, the plurality of temperature sensing elements 322 provide feedback on the interface temperature between the user 104 sitting on the seat 102 and surface A of the seat 102, thereby enabling the determination and control of the user's thermal comfort.

[0044]

[0057] In some embodiments, the system 100 includes a physiological sensor subsystem 232 configured to capture physiological or biometric data associated with user 104. The physiological sensor subsystem 232 includes sensors for capturing and monitoring user 104's physiological metrics (or biometric data). Examples of psychological data include heart rate, heart rate variability, blood glucose level, blood pressure, respiratory rate, body temperature, blood volume, sound pressure, photoplethysmography, electroencephalography, electrocardiogram, blood oxygen saturation, energy expenditure, and skin conductivity.

[0045]

[0058] In some embodiments, the physiological sensor subsystem 232 is designed to work in conjunction with existing physiological data capture devices positioned around the seat 102. For example, if the seat 102 is located inside a vehicle 102, the physiological sensor subsystem 232 is communicatively coupled to sensors or cameras within the vehicle and / or to user devices 114 within the vehicle, such as a vehicle camera, steering wheel sensor, or wearable device. In some embodiments, the seat 102 includes multiple physiological capture devices for capturing physiological data from a user 104 within the seat 102. The physiological capture devices within the seat 102 may include combinations of physiological sensors. For example, the seat 102 may be equipped with skin contact sensors for monitoring gestational serotonin (GSR) and electrocardiogram (EGG).

[0046]

[0059] While examples of "bucket" style seats for use in vehicles have been illustrated and discussed, it should be understood that the principles of the present invention are also applicable to other types of seat assemblies, such as bench seats, baby seats, chairs, sofas, and training benches. Similarly, while examples of use within vehicle seats have been discussed, the present invention is not intended to be limited to vehicle seats.

[0047]

[0060] As shown with reference to Figure 4A, this is a flowchart illustrating an exemplary process 400 for operating seat 102. Process 400 provides steps for establishing the contour of seat 102 based on the size, shape, and personal preferences of user 104. The contour of seat includes adjusting several combinations of bolsters 306a, 308a, lumbar support, multiple bladder 312, seat recline, seat height, and seat angle within the seat adjustment subsystem 230. The contour of seat 102 is based on a combination of manual input from user 104 and / or automatic adjustment based on analysis provided by the computing environment 106 (e.g., performed by conventional software or artificial intelligence) based on an initial assessment of user 104 within seat 102.

[0048]

[0061] First, in step 402, a user profile is optionally created to enable more precise initial adjustments to seat 102. For example, user 104 can create an account and enter a user profile when registering a device (e.g., a vehicle) that houses seat 102 or an application (or app) associated with operating seat 102. User 104 can also edit, update, and review the user profile in a similar manner. A device within system 100 can be used to access the user profile for creation, editing, viewing, etc. For example, the local computing environment may include a touchscreen for accessing and editing the user profile, or an app can be downloaded to the user device 114. The user profile contains data that helps the computing environment 106 learn the user's preferences, evaluate user 104, and provide personalized adjustments to seat 102 to optimize user 104's comfort. Alternatively, user 104 may operate seat 102 without creating a profile, and the method begins in step 404.

[0049]

[0062] When user 104 sits in seat 102, the pressure between user 104 and seat 102 is assessed (step 404). The assessment is provided by activating multiple pressure sensors 134 when the seat back 308 and seat base 306 are occupied by user 104, as discussed with respect to Figure 3G. In some cases, the assessment is activated when the total load generated by the multiple pressure sensors 134 is greater than a predetermined value. For example, if the calculated total pressure load on seat 102 exceeds 36 kilograms, the assessment is initialized.

[0050]

[0063] In step 406, pressure data from the activated pressure sensors 134 are electronically configured to represent the physical locations of the original values ​​in the seat interface mapping. For example, pressure values ​​at each location within the seat 102 are measured and mapped to specific locations within the seat 102. The pressure values ​​at each location can be laid out in a grid (see Figures 4B and 4C) defined by the physical locations of the sensors within the seat 102. The grid of pressure values ​​provides an initial pressure map of the user 104 that represents the location and posture of the user 104's body. The pressure values ​​may be static values ​​captured at a specific point in time, or they may be a collection of values ​​(dynamic data) collected over time. The pressure map is stored in the user profile for future reference. In some embodiments, the pressure map is periodically updated over time and compared with previously stored pressure maps.

[0051]

[0064] In step 408, the pressure values ​​are electronically overlaid onto a pressure grid representing local body mapping zones of the human body model. A given human body model is provided that includes multiple zones for mapping various pressure values, as shown with reference to Figure 4B. Specifically, Figure 4B provides a visual representation of how the human body can be divided for the purpose of pressure distribution. System 100 stores an ideal pressure distribution for each of the sections being depicted (the number of sections is changeable / modifiable) and attempts to achieve the ideal pressure by inflating / deflating the bladder and / or adjusting the layout of the entire seat based on the defined sections. The multiple zones in the human body model correspond to different sections of a person sitting in the seat 102. For example, as depicted in Figure 4B, the human body model may include 17 predetermined zones, from zones 1 and 2 corresponding to the shoulders to zones 16 and 17 representing the lower hamstrings. As will be recognized by those skilled in the art, the human body model may include a different number of zones, and may include zones for the head, arms, legs, etc., although not depicted in Figure 4B. The pressure values ​​for each zone can be represented by individual sensors or by the sum or average of multiple sensors. For example, Zone 1 may include a single pressure sensor associated with that zone, or multiple sensors representing that zone. Similarly, each zone may include a different number of sensors. For example, Zone 1 may include multiple sensors, while Zone 8 may include a single sensor.

[0052]

[0065] In some embodiments, the computing environment 106 is configured to analyze pressure maps and grids to identify different body parts of user 104. In one example, the computing environment uses artificial intelligence / machine learning to identify where user 104's body parts are located and what body parts they are, based on pressure values ​​from multiple pressure sensors 134. A human body model is associated with user 104. In some embodiments, the maps and / or human body model may be updated based on user 104. For example, a heavier or taller user may have more zones than a lighter or shorter user. The human body model can be created based on prior information obtained about the user, or during a configuration step when user 104 sits in seat 102 and the computing environment 106 creates zones, grids, models, etc., of the user profile. Alternatively, the human body model can be generic, applicable to all users, specific genders, size ranges, etc.

[0053]

[0066] In step 410, the mapping of pressure values ​​to a human body model is scaled to fit user 104. Scaling is performed using a method that identifies how pressure values ​​correspond to different zones within the human body model. In some embodiments, the computing environment 106 automatically adjusts the human body model to fit the size and shape of user 104. Figure 4C illustrates, for example, a typical example of pressure distribution in the thigh and buttock regions, related to Figure 4B. Figure 4C illustrates how zones are defined and can be applied to the pressure distribution dataset to divide the seat 102 and adjust to achieve an ideal pressure distribution. For example, as depicted in Figure 4C, the buttocks and legs can be identified by their shape, and zones corresponding to the buttocks (e.g., zones 10, 11) and zones corresponding to the legs (e.g., zones 13-17) can be adjusted so that the activated pressure sensor 324 matches those zones. Scaling is performed using a combination of pressure distribution analysis, advanced occupancy detection, and artificial intelligence. In some embodiments, the user's size and shape are determined using a combination of inputs. For example, the user's size and shape can be determined using seat pressure sensing, images from a camera, and data from the feedback device 110 and / or user device 114 (e.g., a wearable).

[0054]

[0067] In step 412, local pressure values ​​within groups of the human body model are aligned. For example, the gluteal regions 10 and 11 are centered around the ischial tuberosity (IT) pressure peak.

[0068] In step 414, body segment pressures for the user are calculated, corresponding to the zones / models and grids from steps 408 and 410. The body segment pressure calculation may include a combination of pressure calculations, such as percentage load, peak pressure, average pressure, and pressure gradient. In some embodiments, the average and peak pressures of a predefined zone (e.g., Figure 4B) are determined and compared to ideal values. Each pressure calculation can be performed using data from individual pressure sensors 324 or groups of pressure sensors 324 (e.g., pressure sensors in each zone or throughout the entire seat). In some embodiments, the pressure for each segment / zone is calculated. Once the body segment pressure calculations are performed, additional analysis is performed. In some embodiments, the pressure calculations are used to compare the measured values ​​to the ideal pressure distribution for each predefined zone, and the system is adjusted based on this comparison.

[0055]

[0069] In step 416, the left and right sides of the mapped / scaled human body model are analyzed to determine whether they are similar. For example, the left hip (e.g., zone 10) and leg (e.g., zones 12-16) are compared to the right hip (e.g., zone 11) and leg (e.g., zones 14-17) to determine if they are substantially equal. If these values ​​are not similar within a given threshold, process 400 proceeds to step 420. If they are similar, process 400 proceeds to step 422. In step 420, it is determined whether the difference can be explained based on other factors. These factors depend on where user 104 is sitting and the activities user 104 is performing. Driver factors may differ from passenger factors. For example, the difference between the left leg value and the right leg value may be explained by user 104 (e.g., driver) pressing the accelerator or brake pedal in the vehicle. In some embodiments, the difference is explained by taking multiple measurements in sequence to determine if there is a significant change, or by using AI and advanced data acquisition. If the difference between the left and right sides is explained, the process ends in step 424. If the difference cannot be explained, process 400 proceeds to step 426.

[0056]

[0070] Returning to step 422, the pressures on the left and right sides are averaged. The left and right pressure averages can include individual zones or multiple zones. For example, to determine if there is an imbalance from left to right, the average of zones 10, 13, and 16 on the left side (in Figure 4B) can be calculated. In step 426, the equalization pressure for the difference between the two sides is determined. Different pressure equalization processes can be performed to equalize the pressure between the two sides. For example, the pressure on one of the two sides can be adjusted to match the pressure applied to the other side, or the pressure on both sides can be adjusted until equilibrium is achieved. In some embodiments, equalization is determined based on user preference (e.g., from a user profile). For example, if the left side is harder than the right side, but the right side is within the range of hardness desired by user 104, it would be determined that the hardness of the left side needs to be adjusted to match that of the right side. Once the method for equalizing the pressure has been determined, process 400 proceeds to step 428.

[0057]

[0071] Returning to step 418, the local pressure analysis is compared to a predetermined recommended pressure output to determine whether there is a significant difference between the measured pressure metric and the target pressure metric. In some embodiments, the values ​​calculated during step 414 are compared to ideal pressure values ​​obtained from a combination of documented studies, empirical data, and / or AI to determine whether there is a significant difference between the measured pressure metric and the target pressure metric. If the difference between the existing pressure in seat 102 and the ideal pressure exceeds a predetermined threshold, the system will suggest adjustment. If there is no significant difference (for example, if the difference is below a predetermined threshold), process 400 proceeds to step 436, where the current seat contour configuration is saved to the user's profile, and process 400 terminates. If there is a significant difference, the process proceeds to step 428 for seat adjustment.

[0058]

[0072] In step 428, a determination is made as to whether or not to perform the recommended automatic seat adjustment 102 for user 104. For example, the display device 112 may provide user 104 with a prompt including approval of the recommended changes. If no changes are needed or desired, process 400 proceeds to step 436, the current seat contour configuration is saved to the user's profile, and process 400 terminates. If the recommended changes are approved in step 428, the computing environment 106 proceeds to step 430. In some embodiments, the automatic seat adjustment is based on the assessed size, shape, and individual preferences of user 104, which are entered by user 104. A combination of user profiles, pressure and position sensors, and other feedback (e.g., cameras, biometric data, etc.) can be used to determine the automatic seat adjustment. User 104's size and shape are determined in step 410. The automatic seat adjustment also includes changes based on steps 416-426. Individual preferences can be assessed by data collection, artificial intelligence, or a combination of user profiles. Recommended seat adjustments can be provided based on an analysis of user 104's pressure sensor readings and a combination of user 104's individual preferences stored in system 100.

[0059]

[0073] In step 430, once the recommended seat adjustment is approved, the seat 102 is adjusted based on the recommendation. In some embodiments, the adjustment is carried out by a combination of the seat comfort module 130 and the seat adjustment subsystem, changing the pressure of one or more of the multiple bladder 312 and / or the position of at least one of the seat 102 itself, the seat base 306, the seat back 308, or the headrest 310 (including vertical / horizontal movement, lumbar support, bolster, recline, etc.).

[0060]

[0074] In step 432, the seat adjustment is evaluated / re-evaluated after a predetermined period. In some embodiments, the adjustment evaluation step includes prompting user 104 whether to input any comfort changes that user 104 would like to make to the current seat contour configuration. Alternatively, system 100 monitors manual changes made by the user within a predetermined period, as provided in step 434. If no additional comfort changes are made after the predetermined period, process 400 proceeds to step 436, the current seat contour configuration is saved to the user's profile, and process 400 terminates. If the user chooses to make changes, process 400 proceeds to step 434.

[0061]

[0075] In step 434, user 104 manually inputs or requests system 100 to provide further adjustments to the seat contour configuration. In some embodiments, the changes requested by user 104 are analyzed using AI to improve future comfort or recorded in the user's profile for future reference. The contour created by the multiple bladder 312 is adjusted by system 100 and / or user 104 by inflating / contracting a single bladder or cluster of bladders by applying or releasing pressure to specific surface areas of the seat 102. For example, user 104 may apply pressure to the left shoulder area to contract the contour-forming bladder, or release pressure to the same area to inflate the bladder 312 in that area, filling the gap between user 104 and seat 102. For example, computing environment 106 detects (e.g., via sensor 134) that user 104 is intentionally or unintentionally applying or releasing pressure from a particular location and adjusts the bladder 312 accordingly. Multiple bladder 312 can also be adjusted manually via various user inputs to system 100. For example, the user can activate switches on seat 102 or select a section of the graphic representation of seat 102 on display unit 112 or user device 114 to update the contour of seat 102 in a specific area. Once the changes are complete, process 400 proceeds to step 436, where the current seat contour configuration is saved to the user's profile and process 400 terminates.

[0062]

[0076] In step 436, all data from the previous step is stored, including the size, shape, and preferences of user 104, and the final contour of seat 102. In some embodiments, recommendations, user responses, and manual / automatic changes that occur throughout process 400 are stored by the computing environment and used for training / updating the AI / machine learning model. In some embodiments, after the steps in process 400 are performed, seat contour validation is performed and the AI ​​model is trained to optimize future seat contour recommendations. In some embodiments, further analysis of user 104 is performed to confirm the optimal contour of seat 102. Confirmation can be based on manual feedback from user 104 or can be obtained automatically by observation of user 104 and / or physiological data collected about user 104. Manual feedback is provided in the form of a survey or questionnaire completed by user 104, while automatic confirmation is provided by sentiment analysis based on user 104's physiological data (e.g., heart rate, facial recognition, etc.).

[0063]

[0077] In some cases, process 400 is performed automatically when user 104 sits in seat 102. Upon sitting, an initial user pressure and posture assessment is performed to personalize seat adjustments, at least partially, based on the measured size and shape of user 104. Once the assessment is complete, user 104 is presented with a seat personalization prompt, and if seat personalization is approved, the seat contour is automatically adjusted by adjusting multiple bladder 312 based on the pressure and posture assessment. This operation provides a simplified seat adjustment mechanism, saving user 104 time by eliminating the need to manually adjust multiple different aspects of seat 102. In addition, the use of pressure sensors 324 and multiple bladder 312 enables optimized comfort through a higher level of seat contouring than conventional seats. Furthermore, this contouring is designed to properly support the occupant for long-term comfort, rather than relying solely on user 104's own input for the contouring of seat 102. Process 400 records past comfort settings (for example, in the user profile) provided by user 104, along with automatic pressure and posture assessments, so that machine learning can be used to further optimize future recommendations.

[0064]

[0078] A flowchart illustrating the dynamic comfort control of seat 102 and / or the area surrounding seat 102 is shown in Figure 5A. Dynamic comfort control is a continuous operation based on a combination of factors including the comfort, health, and emotional state of user 104 sitting in seat 102. Dynamic comfort control is provided to monitor user 104's condition, adjust seat 102 to be comfortable, and provide recommended actions to user 104 as needed.

[0065]

[0079] In some embodiments, continuous monitoring is performed using various pressure readings captured by multiple pressure sensors 324 and physiological parameters captured by physiological sensors. Pressure and physiological data are used to detect several predefined triggers, such as increases or decreases in seat pressure, restlessness, temperature changes, occupant emotional state (e.g., based on facial recognition, biometrics, etc.), and posture detection. Process 500 responds to different combinations of measured pressure and / or physiological parameters by suggesting or performing adjustments to the contour of the seat 102 and / or recommending other treatments. Treatments include, for example, adjustments to the seat contour, adjustments to the seat-occupant interface temperature and airflow, adjustments to the seat-occupant interface pressure, and unique variations of massage patterns in conjunction with overall posture correction. Massage patterns include any combination of massage type and mechanism for providing the massage. For example, a massage can be provided in any combination of a massage bladder 314 and a haptic feedback device 110 (e.g., rollers).

[0066]

[0080] Process 500 includes adjusting the seat 102 using the seat adjustment subsystem 230 and monitoring the user 104's condition using a combination of multiple pressure sensors 324 and a physiological sensor subsystem 232. If user 104's discomfort or another negative condition is identified or detected, process 500 initiates recommended seat adjustment 102 and / or action. Recommended seat adjustment 102 and / or action may include contour adjustment using the seat adjustment subsystem 230, providing haptic feedback to user 104 using the haptic feedback subsystem 234, providing temperature control for user 104 using the temperature subsystem 236, providing A / V feedback using the A / V feedback subsystem 238, or a combination thereof, as will be discussed in more detail with respect to Figures 4A and 6-12.

[0067]

[0081] First, in step 502, the user's preferences are configured and recorded in the computing environment 106, for example, in an optional user profile. An optional user profile can be created for more precise initial adjustment of the seat 102. User preferences may include selecting options regarding how seat comfort adjustments are set up and / or performed. For example, user 104 can interact with the seat 102 or HMI to configure the seat 102 and define preferences regarding how and when the seat 102 is modified (e.g., contour, haptic feedback, voice feedback, etc.). In some embodiments, user preferences include initial comfort settings and long-term comfort settings. Initial comfort settings can provide user 104 with the option to select manual adjustment of the seat 102 or automatic adjustment of the seat 102 in response to discomfort and / or treatment triggers. In the case of manual seat adjustment, user 104 can adjust the seat 102 using a combination of buttons, switches, a graphical user interface, etc., and manually adjust different parts of the seat 102 as needed. For automatic seat adjustment, user 104 chooses whether to enable or disable automatic seat adjustment, as discussed with respect to Figure 4, for example. If automatic seat adjustment is enabled, user 104 chooses whether to enable it once (e.g., during initial setup) or always enable it. Both the option to set it up once and the option to always enable it are saved in the user profile, and process 400 is executed to establish the “static” comfort configuration of seat 102. Alternatively, user 104 operates seat 102 without creating a profile / preference selection and begins in step 504.

[0068]

[0082] In some embodiments, as part of user preference, user 104 can choose whether or not to operate seat 102 for comfort adjustment. Surface adjustment of seat 102 includes modifying the contouring of seat 102, for example, as discussed with respect to Figure 4A. In some embodiments, the contouring of seat 102 is based on a combination of manual input from user 104 and artificial intelligence provided by computing environment 106 based on user 104's initial assessment. Similar to the selection of automatic seat adjustment, user 104 can choose to enable or disable seat 102 contouring. If seat 102 contouring is enabled, user 104 can choose whether seat 102 contouring is enabled once (for example, during initial setup) or always enabled. Both the once-set-up option and the always-enabled option are stored in the user profile.

[0069]

[0083] In step 504, process 500 performs a pressure scan of the seat 102 to establish an initial baseline pressure. In some embodiments, the pressure scan includes performing the steps of process 400 to establish an initial contour static comfort configuration of the seat 102. In some embodiments, the baseline pressure scan is performed using an interactive seat contouring process 540, as discussed in Figure 5B. Process 540 is started automatically or can be started by user 104 by selecting interactive seat contouring from a menu on a graphical display associated with system 100, for example. In some embodiments, other feedback from the user can be obtained to establish the baseline. For example, in a vehicle, cameras may be used to detect the user's position, the user's emotional state, etc.

[0070]

[0084] As shown with reference to Figure 5B, in step 542 of process 540, interactive seat contouring for user 104 is initiated. Interactive seat contouring requires physical input from user 104 by physically interacting with the seat 102 itself, providing input to areas of the seat 102 that user 104 wishes to modify. For example, user 104 can press harder (e.g., from the bladder 312 at that location) to an area of ​​the seat 102 where user 104 wishes to reduce pressure. Once initiated, interactive seat contouring monitors the overall pressure level of the seat 102 (e.g., via the pressure sensor 324) and identifies areas that user 104 may indicate for adjustment.

[0071]

[0085] In step 544, process 540 determines that user 104 is applying sustained pressure to one or more areas of seat 102. The areas under sustained pressure by user 104 may reflect areas where user 104 wishes to reduce stiffness. In some embodiments, sustained pressure is determined by comparing an initial pressure level (e.g., a pressure level from a pressure scan from step 504) to a current pressure level that has risen above a predetermined threshold over a predetermined period of time. For example, if one or more pressure sensors 324 in seat 102 detect a localized pressure increase of more than 40% for more than 2 seconds (by user 104 applying additional pressure to that area), it is determined that the user is indicating an area where stiffness should be reduced.

[0072]

[0086] In step 546, if user 104 determines that a region needs to be stiffened, process 540 begins to stiffen at least a portion of the seat 102 in the identified region. In some embodiments, the stiffening is achieved by contracting one or at least a portion of a plurality of bladders 312 within the identified region. Once a region for pressure reduction is identified, process 540 contracts at least a portion of all bladders 312 within that region substantially simultaneously, or contracts one or more of the bladders 312 at a time while cycling through all bladders 312 within the identified region. Regardless of the number of bladders 312 adjusted within a given period, process 540 can continue evaluating the target region for adjustment until the appropriate adjustment is achieved.

[0073]

[0087] In some embodiments, process 540 includes an alternative path for a request initiated by user 104 due to increased pressure in one or more areas within the seat 102. The alternative path includes steps 548 and 550. In step 548, process 540 determines that user 104 is applying lower pressure or no pressure to areas within the seat 102 where a higher level of pressure was previously applied. Areas where user 104 is applying lower pressure or no pressure at all may reflect areas in the seat 102 where user 104 wants to increase the stiffness. In some embodiments, lower pressure is determined by comparing an initial pressure level (e.g., a pressure level from a pressure scan from step 504) with a current pressure level that has decreased by more than a predetermined threshold over a predetermined period of time. For example, if one or more pressure sensors 324 in the seat 102 detect a localized pressure drop of more than 40% (due to the decrease in pressure applied by the user) for more than 2 seconds, it is determined that the user indicates an area to increase stiffness.

[0074]

[0088] In step 550, if user 104 determines that a region of increased stiffness is indicated, process 540 initiates an increase in the stiffness of at least a portion of the seat 102 in the identified region. In some embodiments, the increase in stiffness is achieved by inflating one or at least a portion of a plurality of bladders 312 within the identified region. Once a region for pressure increase is identified, process 540 may inflate at least a portion of all bladders 312 within that region substantially simultaneously, or inflate one or more of the bladders 312 at a time while circulating through all bladders 312 within the identified region. Regardless of the number of bladders 312 adjusted within a given period, process 540 may continue evaluating the target region for adjustment until the appropriate adjustment is achieved.

[0075]

[0089] In step 552, process 540 determines that the adjustment of the bladder 312 is complete. For the contraction process (e.g., steps 544-546), at least one of the multiple bladders 312 is contracted until it is completely contracted or until user 104 stops applying the rising pressure. For the expansion process (e.g., steps 548-550), at least one of the multiple bladders 312 is expanded until it is completely expanded or until user 104 begins applying normal pressure or until the gap is filled. In some embodiments, if it is no longer possible to modify (e.g., expand or contract) the bladder 312 in the identified area, process 540 operates one or more bladders 312 from a surrounding location adjacent to or close to the identified area. For example, if user 104 is applying sustained pressure to an area containing three pressure sensors 324, and all bladder 312s associated with those pressure sensors 324 are substantially deflated, then the bladder 312 adjacent to each of the deflated bladder 312 can be initiated to deflate. The same operation exists for bladder expansion. In some embodiments, the determination that adjustment is complete is an iterative process in which a check is performed, and if adjustment is not complete, process 540 returns to a previous step, for example, step 546 or process 550. If adjustment is complete, process 540 proceeds to step 554.

[0076]

[0090] In step 554, process 540 determines whether additional adjustments are needed or desired by user 104. The determination of whether additional adjustments are needed can be made automatically by the computing environment 106 or manually received from user 104 input. An automatic determination that additional adjustments are needed can be triggered based on one or more observed parameters relating to user 104. For example, user 104 applies increased pressure to a different area. Manual input from user 104 is provided, for example, in response to a prompt to user 104 (e.g., via display device 112 or user device 114) regarding whether user 104 desires further comfort changes. If it is determined that further adjustments are needed or desired, process 540 returns to interactive seat contouring in step 542. Otherwise, if no further changes are needed, process 540 terminates and returns to process 500, for example, step 506.

[0077]

[0091] Returning to process 500 in Figure 5A, process 500 initiates a dynamic comfort monitoring state in step 506. In step 506, process 500 continuously monitors the comfort state of user 104 while user 104 is seated in seat 102. In some embodiments, user 104's comfort state is monitored by a combination of time, pressure, restlessness detection, interface temperature, emotion detection, biometric data, and user input. User 104's comfort is determined by a combination of identifying signs of discomfort and user 104's emotional assessment.

[0078]

[0092] In some embodiments, as part of dynamic comfort monitoring in step 506, process 500 monitors the discomfort and / or emotional state of user 104 sitting in seat 102. In some embodiments, user 104's discomfort and / or emotional state is monitored by a combination of feedback from multiple physiological (or biometric) sensors, cameras, microphones, etc., within the physiological sensor subsystem 230. For example, system 100 can utilize a combination of facial recognition analysis, ECG data, and GSR data to determine physiological data such as heart rate, heart rate variability, respiratory rate, stress, pain / discomfort, etc., during emotional state analysis. The discomfort and / or emotional state is used to determine whether seat pressure-specific treatment recommendations are appropriate, as will be discussed in more detail herein.

[0079]

[0093] In some embodiments, as part of the dynamic comfort monitoring state in step 506, process 500 monitors the seat pressure of user 104. The seat pressure is monitored using a plurality of pressure sensors 324. One or more user discomfort states can be triggered based on several combinations of monitoring user 104's comfort, user 104's emotional state, and seat pressure 102. In some embodiments, the discomfort state includes detecting an asymmetric pressure distribution (step 508), detecting changes in user 104's posture (step 510), detecting localized pressure increases by user 104 (step 512), detecting high-pressure points of user 104 (step 514), and detecting restlessness of user 104 (step 516).

[0080]

[0094] In step 508, the detection of an asymmetric pressure distribution of user 104 is triggered. An asymmetric pressure distribution occurs when user 104 is determined to prefer one side over the other while sitting in seat 102. The asymmetric position can be detected by various methods, for example, by comparing the pressure levels on the left and right sides of user 104. In some embodiments, as discussed with reference to Figure 4A, the process for detecting the asymmetric pressure distribution can be triggered and improved after steps 414-428.

[0081]

[0095] In step 510, a change in the user 104's posture is detected. A change in posture occurs when the user 104 moves from one seating position to another while sitting in the seat 102. For example, the pressure distribution between zones in the seat 102 when the user 104 is sitting upright is different from the pressure distribution when the user 104 is sitting hunched over. Changes in posture can be detected in various ways, for example, by comparing the pressure distribution between zones in the seat 102 (applied by the user 104 sitting in the seat) over different periods of time. If a sudden change or gradual shift in the pressure distribution across multiple zones is detected, a change in posture is detected, triggering step 510 and proceeding to step 518.

[0082]

[0096] In step 518, process 500 prompts user 104 whether or not they wish to change the seat contour. If user 104 indicates that they do not wish to change the seat contour, the process proceeds to step 536 and terminates. If user 104 indicates that they wish to change the seat contour, the process proceeds to step 520.

[0083]

[0097] In step 520, process 500 determines whether automatic contouring is enabled. In some embodiments, the enablement of automatic contouring is stored in the user profile. Automatic contouring can be enabled by default initially. If user 104 has enabled automatic contouring, process 500 proceeds to step 522; otherwise, process 500 proceeds to step 524.

[0084]

[0098] In step 522, automatic dynamic contouring is initiated. In some embodiments, dynamic contouring includes making fine adjustments to the entire seating environment so that such changes are barely noticeable to the user (not bothersome or distracting) while being effective in improving the overall feel and comfort of the seat 102, for example, during long-distance travel. Automatic contouring modifies at least one characteristic of the seat 102, such as increasing and / or decreasing (inflating and / or deflating) the pressure within at least one bladder 312, changing the position of the seat 102 itself (e.g., recline, seat angle, seat height, etc.), the seat base 306, seat back 308, lumbar support, bolsters 306a, 308a, headrest 310, etc., and / or activating one of the other subsystems. In some embodiments, the type of automatic contouring is defined by the user's preferences stored in the user profile. In some embodiments, the user profile specifies the selection of the type of automatic contouring to be performed based on a triggered event. For example, user 104 may be provided with prompts to initiate interactive seat contouring, as discussed with respect to Figure 5B, automatic adjustment of the seat contour, as discussed with respect to Figure 4, or manual seat adjustment by the user themselves. In some embodiments, process 400 may also be referred to as a solution for recommendations regarding large pressure changes in seat 102, for example.

[0085]

[0099] In step 524, user 104 is provided with prompts to select the type of contouring to perform. For example, user 104 is provided with prompts to initiate interactive seat contouring, as discussed with respect to Figure 5B, automatic seat contour adjustment, as discussed with respect to Figure 4, or manual seat adjustment by the user. In some embodiments, the computing environment 106 recommends a posture for user 104 to adopt, and then adjusts the seat 102 based on user 104 changing their position to the recommended posture.

[0086]

[0100] In step 512, process 500 detects a localized pressure increase by user 104. A localized pressure increase occurs when the computing environment 106 determines that one or more zones within the seat 102 have accumulated higher pressure than other zones. In some embodiments, the high-pressure zones are compared to a baseline pressure map stored in the user profile. The baseline can be created from interactive seat adjustment, automatic seat contouring, or manually adjusted seat settings created by user 104.

[0087]

[0101] In step 526, in some embodiments, slow, subtle “fine-tuning” of the seat 102's contouring can be performed to counteract pressure increases without warning the user 104. For example, the pressure in the higher-pressure bladder 312 is slightly reduced over a longer period. As the bladder 312 is updated, the system 100 can recalibrate the user 104's comfort accordingly. Fine-tuning can be performed as a precaution before a localized pressure increase is triggered, or in response to a localized pressure increase trigger. For example, in the case of pressure, the seat can distribute the pressure better by fine-tuning over a longer period. The seat can also suggest its own treatment, whether relaxing or energizing, based on emotion detection by analysis of the camera system and / or biometric input.

[0088]

[0102] In step 528, process 500 determines whether the pressure rise is sustained. In some embodiments, a sustained local pressure rise is determined by comparing the pressure after the fine-tuning (or other relaxation modification) is performed to a baseline. If the local pressure rise is sustained, process 500 proceeds to step 530; otherwise, process 500 proceeds to step 536.

[0089]

[0103] In step 530, one or more treatments are recommended to the user 104. The user 104 can choose to select one of the recommended treatments or to reject the treatment suggestion, and if rejected, the process ends in step 536. In some embodiments, the recommended treatments include a selection from seat contour adjustment as provided in Figure 4 or Figure 5B, pneumatic massage, vibration massage, music massage, biometric massage as provided in Figure 6), heart rate-based stress relief as provided in Figure 7, music massage as provided in Figure 8, interactive exercise as provided in Figures 9 and 10, yoga as provided in Figure 11, or heating / cooling treatments as discussed in more detail herein.

[0090]

[0104] In step 532, process 500 receives a selection of actions from user 104. User 104 can select multiple actions, and some actions may be combined. The actions can include any combination of actions discussed with respect to Figures 5B to 12. For example, user 104 can select a music massage using the HMI in the vehicle. Upon receiving the selection from user 104, the computer environment 105 executes the corresponding action. Continuing this example, selecting a music massage triggers the execution of process 800 in Figure 8.

[0091]

[0105] In step 534, process 500 prompts user 104 whether they want to save the triggered user discomfort state and the corresponding treatment selection. If user 104 chooses to save the history, the discomfort state and the corresponding treatment are saved in the user profile. For example, if user 104 selects music massage to alleviate a pressure point, that preference is saved in the user profile.

[0092]

[0106] In some embodiments, step 534 includes activating user profile settings so that user 104 is not prompted to save history each time an event is triggered. Instead, user 104 is given a preference for whether all data is saved, no data is saved, or a combination of some data is saved. In some embodiments, as will be discussed in detail herein, a set of preferred actions for different triggered user discomfort states is provided to the user, or the computing environment 106 can use AI / machine learning to determine which action user 104 prefers and / or which action is most effective in alleviating the problem. Similarly, the computing environment 106 can use AI / machine learning to adjust a menu of shorter actions in the future using user 104's recorded optional selections. For example, if user 104 does not select music massage, music massage is removed from the recommended actions displayed to user 104.

[0093]

[0107] In step 514, process 500 detects a high-pressure point for user 104. A high-pressure point occurs when the pressure level in one or more zones exceeds a predetermined level, defining an unacceptable peak pressure. The trigger for a high-pressure point can be triggered based on a single pressure sensor or on a zone or region of pressure sensors, depending on the desired level of sensitivity. Once the trigger for a high-pressure point is initiated, the process proceeds to step 526 and the corresponding steps, as discussed above.

[0094]

[0108] In step 516, process 500 detects restlessness in user 104. In some embodiments, restlessness is detected by identifying a series of small pressure shifts (smaller than changes in posture) in the seat 102. Once the restlessness trigger is initiated, the process proceeds to step 530 and the corresponding steps, as discussed above. Depending on the configuration, restlessness is triggered when user 104 is feeling nervous or restless due to discomfort. Depending on the type of restlessness, the recommended treatment may differ. For example, for restlessness due to discomfort, an automated or interactive seat contouring process may be recommended, while for nervous restlessness, a game or yoga process may be recommended to calm user 104.

[0095]

[0109] In some embodiments, other forms of treatment are provided, including, for example, a circulatory comfort profile, adjustment of the seat 102 for a new posture, and instruction of the user 104 (e.g., via the display 112 or user device 114) through stretching exercises. In some embodiments, an onboard camera and analysis function are used to provide feedback based on the user 104's visual characteristics and to update AI / machine learning such as contouring and treatment recommendations based on the visual characteristics. For example, the camera and analysis function visualize the user 104 after adding stiffness to the bladder 312. If the user 104's facial features indicate user discomfort, the computing environment 106 modifies the contouring again and updates the user profile for future changes.

[0096]

[0110] In step 536, process 500 ends, or in step 506, returns to monitoring the comfort state. Once a treatment is proposed or performed, the results of the treatment are measured and health and comfort are assessed. The assessment of treatment and health can be performed using a variety of methods. For example, the assessment of treatment and health may include verifying user sensation based on biometrics, visual analysis of user 104, and subjective survey feedback from user 104. In one exemplary embodiment, a camera and analysis are used to determine whether the treatment has a positive effect on user 104. Similarly, physiological data can be referenced to determine whether user 104 is somewhat relaxed after the change and / or treatment is performed. In some embodiments, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0097]

[0111] During operation, processes 500 and 530 can be performed automatically when user 104 sits in seat 102. Upon sitting, an initial user pressure and posture assessment is performed, and seat adjustments are personalized, at least partially, based on user 104's size and shape. After the assessment is complete, the state of seat 102 (e.g., pressure sensor 324) and user 104's physiological data are continuously monitored to determine whether an uncomfortable state has been triggered. This includes continuously monitoring user 104's comfort, health, and emotional state while seat 102. Monitoring is performed using various physiological parameters, such as pressure, restlessness detection, temperature, facial expression, and posture detection.

[0098]

[0112] If an uncomfortable condition is triggered, the computing environment 106 initiates mitigation actions such as slowly adjusting the seat 102 in the background or adjusting the position / pressure of the seat 102. In addition, the computing environment 106 can automatically trigger or recommend treatments, including, for example, unique variations of massage patterns, in conjunction with seat contouring, temperature and airflow at the seat-occupant interface, pressure at the seat-occupant interface, and adjustment of overall posture. Continuous monitoring, background contouring, and treatment recommendations are tailored to the specific user 104 and configured to provide long-term comfort while the user 104 is sitting for extended periods. Process 500 also records past comfort settings provided by the user 104 (e.g., in the user profile) and can use machine learning to further optimize recommendations in the future.

[0099]

[0113] Figure 6 illustrates a flowchart depicting an exemplary process 600 for operating the seat 102. Process 600 provides steps for performing a biometric massage treatment using the seat 102. Biometric massage is one of the treatment options that can be recommended to user 104 to reduce stress and discomfort and / or to keep the user active and engaged in an activity (e.g., driving). In some embodiments, biometric massage utilizes biometric signals (or physiological signals) from the seat 102, user device 114 (e.g., wearable device), and / or surrounding area (e.g., vehicle) to determine user 104's physical, mental, and / or emotional state. Once user 104's state is determined, process 600 is used to provide user 104 with a treatment according to user preference. In some embodiments, the biometric signals themselves are used during the treatment. For example, biometric signals such as heart rate, heart rate variability (HRV), and respiratory rate are processed and used to generate interface stimuli, such as those in the haptic feedback subsystem 234, to affect the state of the user 104.

[0100]

[0114] In step 602, process 600 receives input from multiple feedback devices 110. The feedback devices 110 include biometric sensors, physiological sensors, or other devices capable of capturing physiological data. Examples of biometric signals / physiological data include heart rate, heart rate variability, blood glucose levels, blood pressure, respiratory rate, body temperature, blood volume, sound pressure, photoplethysmography, electroencephalogram, electrocardiogram, blood oxygen saturation, energy expenditure, and skin conductivity. In some embodiments, the feedback devices 110 provide historical data for more robust analysis. The computing environment 106 stores, processes, and retrieves the historical biometric signal / physiological data (for example, in memory 122, storage system 108, user device 114, etc.). In some embodiments, the computing environment 106 analyzes the historical tracking data to evaluate the user 104 over the entire period of time that usage is the duration of sitting in seat 102.

[0101]

[0115] In some embodiments, the seat 102 includes one or more feedback devices 110. For example, the seat 102 may include a skin contact sensor for monitoring skin electroresponse (GSR) and an electrocardiogram (EGG) for monitoring heart rate. Data from the feedback devices 110 are provided to the computing environment 106 using various methods. In one example, the feedback device 110 is wirelessly paired with the computing environment 106, and biometric signals / physiological data are shared and transmitted when the feedback device is within range of the computing environment 106.

[0102]

[0116] In step 604, biometric signals / physiological data are analyzed to determine one or more states of user 104 in seat 102. This analysis may include a combination of logic, AI, machine learning, etc., to determine one or more of user 104's physical, mental, and / or emotional states. By monitoring biometric signals / physiological data, deviations from previously established ideal metrics can be detected.

[0103]

[0117] In step 606, process 600 determines whether user 104 is in a negative state. In this example, the computing environment 106 uses biometric signals / physiological data to determine whether user 104 is tired, agitated, anxious, etc., or energetic, happy, normal, etc. Various methods can be used to determine user 104's state. In some cases, user 104's state is determined using HRV and the stress process 700, which are discussed with respect to Figure 7.

[0104]

[0118] Continuing the description of step 606, if process 600 determines that user 104 is not experiencing any negative conditions, process 600 proceeds to step 618 and terminates. In some embodiments, process 600 proposes or performs a treatment based on the measured deviation and / or the negative conditions of user 104. In one example, the treatment includes biometric massage.

[0105]

[0119] In step 608, a biometric signal sample is recorded. The biometric signal sample may be recorded in real time or may be a previously recorded sample associated with user 104, another user, or the generated machine. In some embodiments, the biometric signal sample may include a signal related to user 104's respiration or heart rate. For example, user 104's heart rate signal may be recorded. The recorded sample may be recorded for a predetermined length. For example, the recorded sample may be about 30 seconds long. In some embodiments, the length of the recorded sample may be edited to loop. For example, in the case of a recorded heart rate, the time between heart rates at the end of the recording and the beginning of the recording may be substantially the same as the time between heart rates in the middle of the recording.

[0106]

[0120] In step 610, the recorded signal is filtered. In some embodiments, filtering includes decomposing the signal target data elements. For example, the signal may be filtered to separate the user 104's heart rate or heart rate into a usable format (for example, to create haptic feedback that simulates HR).

[0107]

[0121] In step 612, the rate of the biometric signal sample to be recorded is changed. The rate of the biometric signal sample can be increased or decreased depending on the desired treatment for the negative state identified in step 606. For negative states associated with stress, anxiety, etc., the biometric sample is changed to slow down. For example, the recorded biometric signal may be slowed down to about 80% of its original rate. For negative states associated with drowsiness, low energy, etc., the biometric sample is changed to accelerate. For example, the recorded biometric signal is accelerated to about 20% of its original rate to stimulate the user 104. The modified biometric signal is stored for future use (e.g., in memory 122, storage system 108, user device 114, etc.). In some embodiments, the rate of the modified biometric sample is gradually increased or decreased over a predetermined period. For example, the rate of the recorded biometric sample is adjusted (increased / decreased) by about 5% over the first period and then adjusted again by 5% over subsequent periods. The gradual increase is carried out subtly, in a way that is imperceptible to the user 104, while still providing the same effect at the end of the treatment.

[0108]

[0122] In some embodiments, step 612 can be performed to accelerate or decelerate other treatments within the seat 102. For example, programs such as pneumatic massage, vibration massage, and music massage can be accelerated or decelerated in response to detected negative conditions (i.e., stress, drowsiness).

[0109]

[0123] In step 614, a desired modified biometric sample is triggered to “recreate” the seat 102. In some embodiments, as part of the “recreate,” at least one of the haptic feedback subsystem 234, the temperature subsystem 236, and the A / V feedback subsystem 238 is activated to mimic the biometric signal. For example, in the case of a heart rate biometric signal, one or more haptic actuators or speakers in the haptic feedback subsystem 234 and the A / V feedback subsystem 238 are activated to match the modified heart rate so that the user perceives that they are feeling their own heart rate. In another example, in the case of a respiratory biometric signal, at least one of the multiple bladder 312 can be pressurized and depressurized to mimic the movement of the chest during breathing.

[0110]

[0124] In some embodiments, one or more subsystems are activated to complement the simulated biometric signal. For example, if user 104 is determined to be stressed, subsystem 236 activates cooling within seat 102 to calm user 104. The subsystem is activated in a combination of many locations within seat 102 to provide the desired effect. In one example, for a heart rate biometric signal, a haptic feedback device 318 located behind user 104's chest is activated. In some embodiments, the modified biometric signal and the corresponding subsystem effect are activated for a predetermined period. For example, the subsystem is activated for 5 to 10 minutes. The type and severity of the detected condition may influence the treatment provided during the biometric massage treatment and the duration / intensity of the simulated biometric signal.

[0111]

[0125] In step 616, process 600 determines whether user 104 is still in a negative state. Similar to step 606, the computing environment 106 can use biometric signals / physiological data to determine whether user 104 is still tired, agitated, anxious, etc., or energetic, happy, normal, etc. Process 600 can re-evaluate the same negative state identified in step 606, or all potential negative states. In some embodiments, new biometrics of user 104 are re-evaluated by comparing them to user 104's baseline biometrics when user 104 is in a healthy, "normal" state.

[0112]

[0126] In some embodiments, process 600 assesses the success of a biometric massage treatment by comparing biometric signals measured before, during, and after the treatment with target data based on existing profiles / historical data. Various methods can be used to determine the state of user 104. For example, the HRV and stress processes 700 discussed with respect to Figure 7 can be used. If user 104's negative state returns to within the normal threshold, process 600 terminates. In some embodiments, if user 104's negative state does not return to within the normal threshold, process 600 returns to step 612, and the biometric sample is further modified. In some embodiments, user 104 is prompted to stop or continue the treatment or select a different type of treatment. For example, if user 104 was using haptic responses, they might choose pneumatic responses at this point. If the received user input is to continue the treatment, the process modifies the current treatment. For example, if the biometric sample was originally decelerated, it is further decelerated, and if the biometric sample was originally accelerated, it is further accelerated. For example, biometric signals can be slowed down to 55% of their original recorded speed.

[0113]

[0127] In step 618, process 600 terminates. The termination process may include stopping process 600, returning to the process that invoked process 600 (e.g., process 500), or returning to step 604 for continued monitoring of user 104. Once the treatment is proposed or performed, the results of the treatment are measured and health and comfort are assessed. The assessment of treatment and health can be performed using a combination of various methods. In one example, the assessment of treatment and health includes verifying user sensation based on at least one of biometrics, visual analysis of user 104, and subjective survey feedback from user 104. In one exemplary embodiment, a camera and analysis are used to determine whether the treatment has a positive effect on user 104. Similarly, physiological data can be referenced to determine whether user 104 is somewhat relaxed after the change and / or treatment is performed. In some embodiments, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0114]

[0128] During operation, in the case of biometric massage, one or more biometric signals are captured from the user 104 sitting in the seat 102, and simulated feedback is generated in the seat 102 based on one or more biometric signals. One or more biometric signals are modified to be faster or slower based on the effect desired by the user 104. This combination of effects provides a personalized comfort experience that enhances mood, promotes mental well-being, and helps the user 104 prepare for the desired activity. Process 600 also provides the ability to influence the state of the user 104 by using and processing biometric signals and by using the biometric signals as input to haptic motors, bladder 312, or other systems within the seat 102 or in the surrounding environment that directly interface with the user 104.

[0115]

[0129] As shown with reference to Figure 7, a flowchart is depicted illustrating an exemplary process 700 for evaluating biometric / physiological data. Process 700 provides steps for performing heart rate variability and stress analysis. Heart rate variability and stress analysis are one of the metrics for determining the state of user 104. Process 700 can be used to provide biometric data for use in other processes discussed herein. In some embodiments, process 700 is carried out using a combination of a physiological sensor subsystem 232 and a haptic feedback subsystem 234. The physiological sensor subsystem 232 is used to capture biometric / physiological data, and the haptic feedback subsystem 234 is used to provide a biometric massage element.

[0116]

[0130] In step 702, process 700 receives input from one or more feedback devices 110 and data entered into the user profile, for example, in memory 122, storage system 108, and / or user device 114. In addition, the computing environment 106 can store and retrieve information about user 104 (for example, in memory 122, storage system 108, user device 114, etc.). The biometric data and user information are combined to establish metrics for evaluating user 104. In some embodiments, the feedback device 110 is an ECG, and the user information includes user 104's age, gender, and fitness level.

[0117]

[0131] In step 704, a first HRV is calculated by the computing environment. The first HRV can be calculated using known methods to determine the time interval between heartbeats. The first HRV can be calculated over a predetermined period of time, such as 5 minutes. In some embodiments, the first HRV is calculated while the user 104 is relaxed.

[0118]

[0132] In step 706, the first HRV calculated from step 704 is compared to a standardized HRV value typical of user 104. The standardized HRV value is stored in the computing environment 106 (for example, in memory 122, storage system 108, user device 114, etc.) and may be a predetermined value specific to a person having the same age, gender, and fitness level as user 104. In some embodiments, the standardized HRV value can be retrieved from a lookup table.

[0119]

[0133] If this comparison determines that the HRV values ​​are similar, the calculated first HRV value is normal, no further processing is required, and process 700 proceeds to step 728. If the comparison results in a discrepancy between the predetermined HRV value and the first HRV calculated by user 104, process 700 proceeds to process 708.

[0120]

[0134] In process 708, the user 104's posture is checked. The user's posture 104 can be evaluated using a combination of systems and methods. For example, posture can be detected via interface pressure, in-line pressure sensors, a vision system, etc. In some embodiments, the effectiveness of different postures of the user 104 is evaluated. For example, posture can be evaluated to assess its effect on the user 104's HRV.

[0121]

[0135] In step 710, the calculated first HRV value is used to perform a Fast Fourier Transform (FFT) on the calculated HRV frequency. The FFT is used to convert the first HRV signal into its individual spectral components and provide frequency information about the first HRV signal.

[0122]

[0136] In step 712, the low-frequency (LF) and high-frequency (HF) values ​​are calculated from the FFT of the first HRV signal to create the first LF / HF ratio. A high ratio may indicate that user 104 is experiencing discomfort or stress. A low ratio may indicate that there is no discomfort or stress, or that it is "normal".

[0123]

[0137] In step 714, an action to treat user 104 is activated via seat 102. The action may include any of the actions discussed herein, for example, any of the processes from Figures 4–6 and 8–12.

[0124]

[0138] In step 716, a second HRV is calculated by the computing environment. The second HRV can be calculated using any known method for determining the time interval between heartbeats. The second HRV can be calculated over a predetermined period, such as 5 minutes.

[0125]

[0139] In step 718, the calculated second HRV value is used to perform a Fast Fourier Transform (FFT) on the calculated HRV frequency. The FFT is used to convert the second HRV signal into its individual spectral components to provide frequency information about the second HRV signal.

[0126]

[0140] In step 720, the low-frequency (LF) and high-frequency (HF) values ​​are calculated from the FFT of the second HRV signal to create a second LF / HF ratio. A high ratio may indicate that user 104 is experiencing discomfort or stress, while a low ratio may be considered more normal.

[0127]

[0141] In step 722, the first HRV ratio and the second HRV ratio are compared. This comparison provides an indication of whether the treatment has provided an improvement to the user 104's emotional state. In some embodiments, process 700 determines whether the treatment is effective and / or whether a new treatment should be selected.

[0128]

[0142] In step 724, a prompt ID is provided to user 104 that displays changes in physical / emotional state and gives the user the option to continue the treatment or select a new treatment. For example, a schematic representation of user 104's emotional state is rendered and displayed to user 104 with the pre-treatment, during-treatment, and post-treatment states, along with an indication of where each state should be. Input from user 104 is received from the prompt, and if the choice is to start a new treatment, process 700 proceeds to step 726; if the choice is to continue the previous treatment, it proceeds to step 722; and if the choice is to end the treatment, it proceeds to step 728.

[0129]

[0143] In step 726, user 104 is prompted to select a new action. For example, process 700 can render options for selecting a new action to user 104 on display 112 or user device 114. The new action is a recommendation based on a combination of user preferences (e.g., user profile) and AI / machine learning based on historical data.

[0130]

[0144] In step 728, process 700 terminates. Termination of process 700 may include stopping the process, returning to process 600, or returning to steps 704, 716 for reassessment. In some embodiments, once a treatment is proposed or performed, the results of the treatment are measured and health and comfort are assessed. The assessment of treatment and health may be performed using a combination of methods. For example, the assessment of treatment and health may include verifying user sensation based on at least one of biometrics, visual analysis of user 104, and subjective survey feedback from user 104. In one exemplary embodiment, a camera and analysis are used to determine whether the treatment has a positive effect on user 104. Similarly, physiological data may be referenced to determine whether user 104 is somewhat relaxed after the change and / or treatment is performed. In some embodiments, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0131]

[0145] Figure 8 illustrates and depicts a flowchart illustrating an exemplary process 800 for providing a music-based massage to user 104. Process 800 provides steps for performing a music-based massage using seat 102. The music-based massage can be offered as a form of treatment or used as entertainment, as discussed with respect to Figures 4–6. First, process 800 receives biometric data and emotion recognition input from user 104. The biometric data may include biometric or physiological data as discussed herein, and emotion recognition can be derived by capturing an image of user 104's face using a camera and performing an analysis of the captured image.

[0132]

[0146] In step 802, process 800 assesses the state of user 104, such as physical, mental, and / or emotional states determined using biometric or physiological data and emotion recognition. In some embodiments, the state of user 104 provides indications of boredom, fatigue, stress levels, and happiness.

[0133]

[0147] In step 804, process 800 prompts user 104 whether or not they want to start a music-based massage. This prompt can be provided via display 112 or user device 114 and may include, for example, a graphical icon or other mechanism configured to inform user 104 that a music-based massage may be selected. In some embodiments, this prompt is triggered depending on user 104's state. For example, if user 104 is stressed or tired, computing environment 106 may recommend that user 104 participate in a music-based massage to relax. If user 104 refuses to participate in a music-based massage, process 800 proceeds to step 814 and terminates. If user 104 accepts to participate in a music-based massage, process 800 proceeds to step 806.

[0134]

[0148] In step 806, user 104 is provided with a prompt indicating music-based massage modes for selection. The music-based massage modes are based on different moods, such as energizing, fun, happy, and others. Music-based massage modes can also be selected based on songs or music genres. In some embodiments, each mode / mood is associated with one or more pre-programmed songs or playlists that are synchronized with one or more haptic feedback elements of seat 102 for the overall tactile experience of the massage base. User 104 can select one of the music-based massage modes depending on which mood offered at a given time is appealing. In some embodiments, process 800 provides one or more selection mechanisms via computing environment 106 so that user 104 can manually select custom songs, moods, or playlists or select from an existing user profile. In some embodiments, an upload mechanism is provided so that user 104 can upload their own pre-programmed music-based massages, including songs and feedback such as type, speed, and intensity provided by seat 102.

[0135]

[0149] In step 808, the selected music mode is activated based on a selection made by user 104. For example, if user 104 wants to feel more energetic, user 104 can select an energetic music-based massage mood. Upon activation, seat 102 provides user 104 with haptic feedback corresponding to the selected music. In some embodiments, at least one of the haptic feedback subsystem 234, temperature subsystem 236, and A / V feedback subsystem 238 is activated to provide haptic feedback. For example, in the case of an energetic mood, one or more haptic actuators, bladder 312, massage bladder 314, feedback device 316, or speakers in the haptic feedback subsystem 234 and A / V feedback subsystem 238 are activated / deactivated in sync with the music to provide a music-based massage experience. In some embodiments, music selection is recommended based on the tempo and tone of the music and how they may affect user 104's state. For example, flat keys are generally more associated with sad / depressed moods. In some embodiments, videos can be provided for users other than the driver, synchronized with music. For example, a video with a link that has the desired effect, such as a music video for a song, can be displayed to user 104.

[0136]

[0150] In some embodiments, the music-based massage operates with audio imported from an external source, such as the vehicle radio or user device 114. The music signal is filtered as needed and sent to the seat 102 for output devices such as bladder and / or haptic feedback devices. Filtering may include changing the signal from the music into a format that can be activated by the respective feedback devices. For example, the bass note of a song can be separated as an actuation signal to activate one or more bladder substantially simultaneously with the bass note played by the speaker. In some embodiments, the selected music-based massage operates over a predetermined period of time. In one example, the music-based massage operates one song at a time.

[0137]

[0151] In step 810, process 800 prompts user 104 whether they wish to continue the music-based massage with a different song of the same mood, genre, etc. If the user selects to continue, process 800 returns to step 808 and the next song is played along with the music-based massage. If the user selects not to continue, process 800 proceeds to step 812.

[0138]

[0152] In steps 812 and 814, the music-based massage is stopped. In some embodiments, after stopping the music-based massage, process 800 returns to step 806. Once the music-based massage is performed, the results of the music-based massage are measured and the health and comfort of user 104 are assessed. The assessment of treatment and health is performed based on at least one of the following: biometrics, visual analysis of user 104, and subjective survey feedback from user 104. In one exemplary embodiment, a camera and analysis are used to determine whether the music-based massage has a positive effect on user 104. Similarly, physiological data can be referenced to determine whether user 104 is somewhat relaxed after the music-based massage is performed. In some embodiments, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0139]

[0153] During operation, user 104 selects a pre-programmed song for the music-based massage performed by seat 102. The haptic feedback elements of seat 102 are activated based on the pre-programmed song, creating synchronized haptic feedback responses in time with the music (e.g., the rhythm, beat, etc.). This combination of effects, along with a unique synergy with the haptic massage elements, allows user 104 to truly enjoy the music, resulting in enhanced comfort, among other things. Process 800 also provides the ability to influence user 104's state, improve user experience, build a direct correlation between specific music tracks and user 104's unique emotional state, and create a personalized music library based on favorite songs and their effect on user 104's emotional state.

[0140]

[0154] As shown with reference to Figure 9, a flowchart illustrating an exemplary process 900 for interacting with user 104 in a game is provided. In this example, a version of the game Simon Says is implemented. The Simon Says game can also be offered as a form of treatment or used as entertainment, as discussed with reference to Figures 4–6. First, process 900 receives biometric data and emotion recognition input from user 104. The biometric data and emotion recognition can be obtained using the techniques already described.

[0141]

[0155] In step 902, process 900 assesses the state of user 104. This state may include physical, mental, and emotional states determined based on biometric or physiological data and emotion recognition. The state of user 104 may include the aforementioned states.

[0142]

[0156] In step 904, process 900 prompts user 104 whether or not they wish to begin an interactive exercise or game. The prompt can be provided using the mechanisms and techniques already described. For example, display 112 or user device 114 can display a notification prompting user 104 about available interactive exercises, including Simon Says. In some embodiments, the prompt is triggered depending on user 104's state. For example, if user 104 is stressed or tired, computing environment 106 may recommend that user 104 participate in an interactive exercise to relax. If user 104 refuses to participate in Simon Says, process 900 proceeds to step 914 and terminates. If user 104 accepts to participate in Simon Says, process 900 proceeds to step 906.

[0143]

[0157] In step 906, user 104 is presented with a prompt along with a selection of interactive exercises. Each interactive exercise is associated with one or more activities synchronized with one or more haptic feedback elements on seat 102 for an interactive experience. User 104 can select one of the interactive exercises depending on which is most engaging at a given time. In process 900, the selected interactive exercise is playing a version of Simon Says.

[0144]

[0158] In step 908, the interactive exercise of Simon Says is initiated. During Simon Says' gameplay, in some embodiments, sounds from the seat 102 or its surroundings (e.g., vehicle speakers, user device 114, etc.) are played along with localized haptic feedback. In some embodiments, at least one of the haptic feedback subsystem 234, temperature subsystem 236, and A / V feedback subsystem 238 is activated to provide haptic feedback. For example, one or more haptic actuators, bladder 312, or speakers in the haptic feedback subsystem 234 and A / V feedback subsystem 238 are activated / deactivated in localized areas. The haptic feedback is provided in localized areas so that the user 104 can clearly identify which part of the seat 102 is being activated. In some embodiments, the localized areas containing haptic feedback include the left and right shoulders and the left and right thighs of the seat 102. During gameplay, a random pattern of different activation locations is executed. Depending on the location on the seat, user 104 can respond by applying pressure (sensed by pressure sensor 324 or other sensors) and attempt to reproduce the pattern. To continue playing the game, user 104 must press down on seat 102 according to the location and sequence of haptic feedback provided by the seat in the previous cycle.

[0145]

[0159] In step 910, process 900 determines whether the sequence entered by user 104 matches the sequence provided by seat 102 and provides appropriate feedback. If user 104 does not match the pattern provided by seat 102, a negative response may be provided. In one example, computing environment 106 provides a graphic indicating that the pattern does not match and to try again. If user 104 matches the pattern provided by seat 102, a positive response is provided and the next cycle begins. In one example, computing environment 106 provides a graphic indicating that the pattern matches and renders a celebratory graphic (e.g., fireworks, golden stars). During gameplay, prompts and outputs may be provided via display 112, user device 114, HMI, etc. In some embodiments, data related to gameplay may be stored for access by user 104 and / or process 900. For example, user level, high score, etc., may be stored (e.g., in a user profile) and accessible by user 104.

[0146]

[0160] In step 912, process 900 prompts user 104 whether they want to continue playing Simon Says. If the received choice is to continue, process 900 returns to step 908 and the next round of play begins. If the received choice is not to continue, process 900 proceeds to step 914. In some embodiments, when user 104 finishes playing the game, additional information is displayed to user 104. For example, the player's score, completed rounds, and fitness details such as total calories and average heart rate are displayed to user 104.

[0147]

[0161] In step 914, the Simon Says game is stopped. In some embodiments, after stopping the game, process 900 returns to step 904 to select another interactive exercise or exit the menu. Once an interactive exercise is performed, the results of the interactive exercise are measured and the health and comfort of user 104 are assessed. Assessments of treatment and health can be determined based on at least one of biometrics, visual analysis of user 104, and subjective survey feedback from user 104, using techniques and mechanisms already described with respect to other comfort features. In some embodiments, as also described with respect to other comfort features, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0148]

[0162] As shown with reference to Figure 10, a flowchart is depicted illustrating an exemplary process 1000 for conducting a dance game using seat 102. The dance game can be offered as a form of treatment or used as entertainment, as discussed with respect to Figures 4–6. First, process 1000 receives biometric data and emotion recognition input from user 104. The biometric data may include any combination of biometric or physiological data discussed herein, and emotion recognition can be derived by capturing an image of user 104's face using a camera and performing an analysis of the captured image.

[0149]

[0163] In step 1002, process 1000 assesses the state of user 104. The state may include any combination of physical, mental, and emotional states that can be derived using biometric or physiological data and emotion recognition. In some embodiments, the state of user 104 may include boredom, fatigue, stress levels, and well-being. In some embodiments, the user's biometrics and state are continuously monitored and updated during process 1000.

[0150]

[0164] In step 1004, process 1000 prompts user 104 whether or not they wish to begin an interactive exercise. The prompt can be provided, for example, using display 112 or user device 114. In some embodiments, the prompt is triggered depending on user 104's state. For example, if user 104 is stressed or tired, computing environment 106 may recommend that user 104 participate in an interactive exercise to relax. If user 104 refuses to participate in the dance simulator, process 1000 proceeds to step 1014 and terminates. If user 104 accepts to participate in the dance simulator, process 1000 proceeds to step 1006.

[0151]

[0165] In step 1006, user 104 is presented with a prompt for selection of available interactive exercises. In process 1000, the selected interactive exercise is a dance simulator.

[0152]

[0166] In step 1008, an interactive exercise of the dance simulator is initiated. In some embodiments, a difficulty level of the game is selected. The difficulty level may be manually selected by the user 104, or it may be automatically selected (or recommended) by the computing environment 106, partly based on the user 104's past data (previous performance) and biometric data. In one example, using data from step 1004, if the user 104 has a high heart rate measurement, the computing environment 106 recommends a lower difficulty rating than for the user 104 with a low heart rate measurement. In some embodiments, one or more songs are selected for gameplay. The songs may be manually selected by the user 104, or they may be automatically selected (or recommended) by the computing environment 106, partly based on the user 104's past data (previous performance) and biometric data. In one example, using data from step 1004, if user 104 has a higher heart rate reading, the computing environment 106 recommends songs of a lower intensity level than user 104 would have if the heart rate reading were lower.

[0153]

[0167] During gameplay of the dance simulator, in some embodiments, sounds from the seat 102 or its surroundings (e.g., vehicle speakers, user device 114, etc.) are played along with localized haptic feedback. In some embodiments, at least one of the haptic feedback subsystem 234, temperature subsystem 236, and A / V feedback subsystem 238 is activated to provide haptic feedback. In some embodiments, haptic feedback is enabled or disabled based on user preferences (e.g., stored in a user profile).

[0154]

[0168] During gameplay, randomized patterns of arrows or other shapes are displayed to user 104 (for example, on the HMI, display 112, user device 114, etc.). The arrows or other shapes correspond to dance movements that user 104 performs while sitting in seat 102. As the arrows or other shapes move from one side of the screen to the other, user 104 must mimic that movement in seat 102. In one example, the moving arrow or other shape overlaps with a stationary arrow at the top of the screen. To mimic the movement, at appropriate times (for example, when the shape overlaps the outline), user 104 applies pressure to a specific part of seat 102 (detectable by pressure sensor 324) according to the location and sequence of the displayed shape.

[0155]

[0169] In step 1010, process 1000 determines whether the sequence entered by user 104 matches the sequence provided by the display and provides feedback. In some embodiments, each action or movement by user 104 is assessed independently and assigned a precision rating based on the accuracy of the response to the timing. The computing environment 106 generates positive and negative feedback for user 104 based on the precision assessment. In one example, if user 104 does not match the pattern provided by the display, user 104 is given a negative response. For example, the computing environment 106 provides a graphic indicating that user 104 failed to time the pressure application on the seat 102 with the corresponding shape on the screen. If user 104 successfully matches the pattern provided by the display, a positive response is provided. For example, the computing environment 106 provides a graphic indicating that the user successfully timed the pressure application on the seat 102 with the corresponding shape on the screen. In another example, if user 104 performs a series of successful movements, they may receive a combo certification along with additional praise or encouragement.

[0156]

[0170] In some embodiments, the computing environment 106 displays the level of success for each or many movements in the song in real time, along with a progress bar indicating the degree of success the user is currently achieving. The amount of success may represent the percentage of success required to “complete” or “win” the song. For example, the computing environment 106 records and displays whether a movement was a complete success ("perfect"), a partial success ("great", "great", "good", "almost there"), or a failure ("boo") depending on how off-timing it was or whether it was a complete “miss".

[0157]

[0171] In step 1012, process 1000 prompts user 104 whether or not they want to continue playing the dance simulator. If the received choice is to continue, process 1000 returns to step 1008 and the next round of play begins. If the received choice is not to continue, process 1000 proceeds to step 1014. In some embodiments, when user 104 finishes playing the game, additional information is displayed to user 104. For example, the number of graded contacts (i.e., the number of "perfect," "good," etc.), the final rating or performance grade of the song, fitness rating, HR before and after the song, estimated calories consumed during the song, etc., may be displayed to user 104.

[0158]

[0172] In step 1014, the dance simulator game is stopped. In some embodiments, after stopping the game, process 1000 returns to step 1004 to select another interactive exercise or exit the menu. Once an interactive exercise is performed, the results of the interactive exercise are measured and the health and comfort of user 104 are assessed. The assessment of treatment and health can be performed using the techniques described above. In some embodiments, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0159]

[0173] During operation, user 104 uses seat 102 to select an interactive game of the dance simulator to play. First, before starting the dance simulator, user 104 is asked whether they want to feel the music during gameplay. If they do, the haptic feedback subsystem 234, temperature subsystem 236, and A / V feedback subsystem 238 are activated to provide haptic feedback in music massage mode, allowing user 104 to feel the music while playing the game. The display provides graphics indicating when and where the user should move, synchronized with music playback from the audio output. The pressure sensor 324 (or other sensors) on seat 102 detects the pressure applied to seat 102 by user 104. The computing environment 106 then determines whether the timing and location of the pressure applied by the user match the pattern provided to user 104 on the display. The interactive gameplay provided by the dance simulator provides entertainment, mood enhancement, and promotes physical well-being and health through the activity.

[0160]

[0174] Figure 11 illustrates a flowchart depicting an exemplary process 1100 for conducting a yoga session using seat 102. The yoga session may be offered as a form of treatment or as entertainment, as discussed with respect to Figures 4–6. First, process 1100 receives biometric data and emotion recognition input from user 104. The biometric data may include biometric or physiological data as discussed herein, and emotion recognition can be derived by using a camera to capture an image of user 104's face and performing an analysis of the captured image.

[0161]

[0175] In step 1102, process 1100 evaluates the state of user 104 (including the state described above).

[0176] In step 1104, process 1100 prompts user 104 to input a selection of an interactive exercise. For example, display 112 or user device 114 displays a selectable graphical mechanism listing available interactive exercises, including a yoga session. In some embodiments, the prompt is triggered depending on user 104's state. For example, if user 104 is stressed or tired, computing environment 106 may recommend that user 104 participate in an interactive exercise to relax. As previously mentioned, each interactive exercise is associated with one or more activities synchronized with one or more haptic feedback elements in seat 102 for an interactive immersive experience, and user 104 can select one of the interactive exercises depending on which is most appealing at a given time. However, in process 1100, the selected interactive exercise is a yoga session.

[0162]

[0177] If user 104 refuses to participate in the yoga session, process 1100 proceeds to step 1114 and terminates. If user 104 accepts to participate in the yoga session, process 1100 proceeds to step 1106. In step 1106, the user's selection is received. In step 1108, the interactive exercises of the yoga session begin. In some embodiments, the yoga session interacts with the user by using local audio and / or video to provide prompts, display information, etc. For example, the yoga session may include a video showing user 104 a mimicked pose and giving instructions to user 104.

[0163]

[0178] In some embodiments, the bolsta bladha contracts first, and the seat B-side bladha (seat and cushion) inflates first. These actions provide a flatter surface for yoga. In some embodiments, the A-side bladha inflates in specific areas to support the various poses shown in the video and to simulate breathing timing (inhalation / exhalation). Multiple bladhas 312 can be used to perform different yoga poses and movements. For example, in the case of a twist, in coordination with the timing in the video, one side of the seat 102 bladha inflates and the opposite side of the seat 102 flexes. In another example, when rounding the back, the bladha of the backrest 308 contracts and the shoulder bladha inflates. In the last example, the shoulder bladha contracts and the hip bladha (e.g., of the backrest 308) inflates to support an upright stretch pose.

[0164]

[0179] During a yoga session, in some embodiments, the user 104's respiratory rate and / or heart rate are monitored, and the seat 102 is used to guide the user 104 through breathing exercises via various cues (video, auditory, tactile interfaces, etc.). The cues can be provided directly from the seat 102 or around the seat 102 (e.g., vehicle speakers, user device 114, etc.). In some embodiments, at least one of the haptic feedback subsystem 234, the temperature subsystem 236, and the A / V feedback subsystem 238 is activated to provide the cues. In some embodiments, the process provides the user 104 with real-time audio and / or visual feedback. The feedback can be real-time or pre-recorded feedback to the user to prompt completion of the video (audio from the yoga video) and feedback regarding improvements in biometric signals such as pulse rate and blood oxygen. In some embodiments, the yoga session is programmed to optimize the occupant's posture.

[0165]

[0180] In step 1110, process 1100 prompts user 104 to specify a target region. In some embodiments, computing environment 106 provides recommended yoga types and / or target regions based on user 104's assessed emotional state and biometric data. In one example, computing environment 106 provides a graphic indicating that a particular treatment is recommended.

[0166]

[0181] In step 1112, process 1100 prompts user 104 whether they wish to continue the yoga session. If the received choice is yes, process 1100 returns to step 1108 and continues the yoga session. If the received choice is no, process 1100 proceeds to step 1114. In some embodiments, when user 104 ends the yoga session, additional information is displayed to user 104. For example, fitness details such as respiratory rate, total calories, and average heart rate are displayed.

[0167]

[0182] In step 1114, the yoga session is stopped. As with other embodiments of interactive exercise, the results of the yoga session are measured to assess the health and well-being of user 104. The assessment of treatment and health can be performed based on at least one of biometrics, visual analysis of user 104, and subjective survey feedback from user 104. In one exemplary embodiment, a camera and analysis are used to determine whether the interactive exercise had a positive effect on user 104. Similarly, physiological data can be referenced to determine whether user 104 is somewhat relaxed after performing the interactive exercise. In some embodiments, the feedback provided through these analyses is used to update the AI / machine learning model (e.g., a training model).

[0168]

[0183] During operation, a selection of one or more yoga programs for a yoga session is received from the user input device. The selected yoga program is started, and based on the poses the user is performing, a selected bladder 312 is deflated and another selected bladder 312 is inflated. The computing environment 106 monitors the user 104's progress using one or more of the pressure sensors 324 and feedback devices 110. For example, the computing environment 106 can capture images of the user using one or more cameras and compare the user's form to a given form to determine whether the user 104 is performing the pose correctly. The computing environment 106 also monitors one or more biometric signals of the user 104. For example, the user 104's respiratory rate and heart rate are monitored (for example, using a biometric feedback device 110). Based on the measured biometric signals, the computing environment 106 can provide feedback to the user 104 and / or update yoga instructions to provide the user 104 with positive reinforcement, correction, etc.

[0169]

[0184] As shown with reference to Figure 12, in some embodiments, the temperature subsystem 236 complements one or more of the processes discussed with respect to Figures 3–11. The temperature subsystem 236 provides heating and cooling using temperature control elements 320 and temperature sensing elements 322. In some embodiments, each temperature sensing element 322 controls the temperature at a particular location so that a target temperature (for example, set by the user 104) is achieved throughout the seat 102. The target temperature is maintained by comparing the target temperature to the actual temperature in each zone. If the difference between the two temperatures is less than or greater than zero, the temperature control element 320 at that location is activated to correct the temperature.

[0170]

[0185] As depicted in Figure 12, the temperature subsystem 236 complements other subsystems and treatment processes. The temperature subsystem 236 is configured to provide targeted and customizable heating and cooling throughout the seat 102. Heating and cooling can be provided broadly or to targeted / localized areas within the seat 102. In some embodiments, the computing environment 106 provides an interface for manual control of the target temperature, displaying interface temperatures in various areas within the seat 102, for example, provided by the temperature sensor 322.

[0171]

[0186] In some embodiments, the temperature subsystem 236 is used to establish a target temperature for the seat 102 before the user 104 sits in the seat 102 during the remote startup of the vehicle. In some embodiments, the temperature subsystem 236 is used to continuously monitor the temperature of the seat 102 during dynamic comfort and adjust the temperature as needed to maintain the target temperature throughout the seat 102. In some embodiments, the temperature subsystem 236 is used to complement biometric massage to assist in regulating the temperature of the seat 102 according to biometric massage parameters (e.g., Figure 6). In some embodiments, the temperature subsystem 236 is used to complement interactive entertainment processes (e.g., Figures 8–11). In one example, heat is applied by the temperature control element 320 to warm up the user 104 before starting any of the activities. In another example, cooling is applied by the temperature control element 320 to cool down the user 104 after completing any of the activities.

[0172]

[0187] By using the temperature subsystem 236 in this manner, we can provide personalized thermal comfort, enhanced physiological effects of massage, and an overall enhanced, customizable seating environment.

[0173]

[0188] The following is a list of examples of devices, systems, and methods of the subject matter described and illustrated in the aforementioned specification.

[0189] Example 1: It is a seat, Frame and, Multiple seat cushions, Multiple adjustable bladders located inside the seat, Multiple sensors placed inside the seat, A memory for storing user data and multiple seat adjustment programs for controlling multiple adjustable bladders, A seat comprising a memory, multiple adjustable bladders, and an electronic processor coupled to multiple sensors, wherein the electronic processor is configured to control the multiple adjustable bladders based on user data and feedback from at least one of the multiple sensors, according to a seat adjustment program.

[0174]

[0190] Example 2: The seat of Example 1, wherein the multiple seat cushions include a seat base cushion, a back cushion, and a headrest cushion.

[0191] Example 3: A seat, the same as in Example 1 or Example 2, further comprising multiple temperature control elements.

[0175]

[0192] Example 4: A seat according to Examples 1-3, further equipped with multiple haptic feedback devices.

[0193] Example 5: A seat according to Examples 1-4, further comprising multiple haptic feedback generators.

[0176]

[0194] Example 6: A seat according to Examples 1-5, wherein the multiple sensors include a combination of physiological sensors, pressure sensors, and temperature sensors.

[0195] Example 7: A seat according to Examples 1 to 6, wherein multiple seat adjustment programs include a static comfort module, and an electronic processor is configured to establish the seat contour.

[0177]

[0196] Example 8: The seat in Example 7, and the electronic processor is A seat configured to establish its contours based on the user's size, shape, and personal preferences via a seat adjustment subsystem.

[0178]

[0197] Example 9: A seat according to Example 8, wherein establishing the seat contour via a seat adjustment subsystem includes adjusting a combination of a bolster, lumbar support, multiple adjustable bladder, seat recline, seat height, and seat angle.

[0179]

[0198] Example 10: A seat according to Example 7, wherein an electronic processor is configured to assess the pressure between the user and the seat.

[0199] Example 11: A seat according to Example 10, wherein the electronic processor is configured to determine the total load measured by multiple pressure sensors before assessing the pressure between the user and the seat.

[0180]

[0200] Example 12: The seat of Example 7, wherein the multiple sensors include multiple pressure sensors located in multiple locations, and the electronic processor is configured to generate a map of pressure values ​​based on the pressures sensed by the multiple pressure sensors.

[0181]

[0201] Example 13: A seat from Example 12, where the pressure value map is stored in the user profile.

[0202] Example 14: A seat from Example 12, wherein the pressure values ​​are overlaid on a pressure grid representing localized body mapping zones of a human body model.

[0182]

[0203] Example 15: The seat in Example 7, and the electronic processor is Control the seat pressure scan to establish an initial baseline pressure. A seat configured to establish an initial contour static comfort configuration of the seat via a seat adjustment subsystem.

[0183]

[0204] Example 16: A method for operating a seat, The pressure between the user and the seat is assessed via multiple pressure sensors, The process involves configuring pressure data from multiple pressure sensors to represent a physical location via an electronic processor, The process involves generating a grid of pressure values ​​from pressure data via an electronic processor, and The process involves scaling pressure values ​​to a human body model for the user via an electronic processor, and creating a scaled human body model. Aligning pressure values ​​within a local group of human body models via an electronic processor, The process involves determining the user's body segment pressure via an electronic processor, The process involves analyzing the left-side and right-side pressure values ​​of a scaled human body model via an electronic processor to determine whether the left-side and right-side pressure values ​​are similar within a predetermined threshold, and If the left-side pressure value and the right-side pressure value are similar within a predetermined threshold, the left-side pressure value and the right-side pressure value are averaged. The measured pressure value is compared with the target pressure value, and the difference between the measured pressure and the target pressure is determined. If the difference between the measured pressure and the target pressure exceeds a predetermined threshold, the seat adjustment is performed via the electronic processor. A method comprising storing the current seat contour in a user profile if the difference between the measured pressure and the target pressure does not exceed a predetermined threshold.

[0184]

[0205] Example 17: A method relating to Example 16, further comprising entering user-entered data into a user profile.

[0206] Example 18: The method of Example 16 or Example 17, If the left-side pressure value and the right-side pressure value are not similar within a predetermined threshold, it is determined whether the difference between the left-side pressure value and the right-side pressure value can be explained based on predetermined factors. A method further comprising determining the equalization pressure when the difference between the left-side pressure value and the right-side pressure value can be explained.

[0185]

[0207] Example 19: A method relating to Examples 16-18, wherein performing seat adjustment via an electronic processor includes controlling a seat adjustment subsystem.

[0208] Example 20: A method relating to Examples 16-19, further comprising evaluating seat adjustments after a predetermined period of time.

[0186]

[0209] Example 21: A method relating to Examples 16-20, further comprising, via an electronic processor, displaying a user prompt on a display device before performing seat adjustments, and processing responses to the user prompts.

[0187]

[0210] Example 22: A method for operating a seat, comprising a plurality of adjustable bladders located within the seat, a plurality of sensors positioned within the seat, a memory for storing user data and a seat adjustment program for controlling the plurality of adjustable bladders, and an electronic processor coupled to the memory, the plurality of adjustable bladders, and the plurality of sensors, wherein the electronic processor is configured to control the plurality of adjustable bladders according to the seat adjustment program, based on user data and feedback from at least one of the plurality of sensors, and this method is... Adjusting the seat via an electronic processor and seat adjustment subsystem, The system monitors the user's condition through an electronic processor and a combination of multiple pressure sensors and physiological sensor subsystems. Configuring user preferences, Perform a seat pressure scan to establish an initial baseline pressure, Receiving physical input from the user via the seat and multiple pressure sensors, To determine whether the user is applying sustained pressure to the first area of ​​the seat, In response to determining that the user is applying sustained pressure to a first area of ​​the seat, the firmness of the first area of ​​the seat is reduced. To determine whether the user is applying significant pressure to the first area of ​​the seat, A method comprising determining that the user is not applying much pressure to a first area of ​​the seat, and increasing the firmness of a seat area.

[0188]

[0211] Example 23: The method of Example 22, further comprising adjusting the firmness of a second area of ​​a seat adjacent to a first area of ​​a seat.

[0212] Example 24: A method relating to Example 22 or Example 23, further comprising determining whether additional adjustments to the seat are necessary.

[0189]

[0213] Example 25: A method relating to Examples 22-24, further comprising monitoring the user's comfort state.

[0214] Example 26: A method relating to Example 25, wherein the user's comfort state is determined via an electronic processor based on a combination of time, seat pressure, seat temperature, and biometric information.

[0190]

[0215] Example 27: A method of Example 22, further comprising determining the user's emotional state via an electronic subsystem and a physiological subsystem.

[0216] Example 28: The method of Example 22, further comprising determining the user's seat pressure via an electronic processor and a plurality of pressure sensors.

[0191]

[0217] Example 29: A method relating to Example 28, further comprising determining an asymmetric pressure distribution via an electronic processor.

[0218] Example 30: A method of Example 22, further comprising determining changes in the user's posture via an electronic processor and a plurality of pressure sensors.

[0192]

[0219] Example 31: A method of Example 22, further comprising determining a localized pressure increase by a user via an electronic processor and a plurality of pressure sensors.

[0220] Example 32: The method of Example 22, further comprising determining the user's high-pressure point via an electronic processor and a plurality of pressure sensors.

[0193]

[0221] Example 33: The method of Example 22, further comprising determining whether a user is restless via an electronic processor and a plurality of pressure sensors.

[0222] Example 34: The method of Example 22, further comprising prompting the user via an electronic processor and output device to indicate whether or not the user wants to change the contour of the seat.

[0194]

[0223] Example 35: The method of Example 34, The system receives an indication via an input device and electronic processor that the user wants to change the seat contour, A method further comprising initiating automatic contouring of a seat.

[0195]

[0224] Example 36: The method of Example 35, wherein automatic contouring includes at least one selected from the group consisting of changing the inflation of at least one of a plurality of bladders, changing the position of a seat, changing the position of the seat base of the seat, changing the position of the seat backrest, changing the position of the lumbar support, and changing the position of the seat headrest.

[0196]

[0225] Example 37: A method relating to Example 22, further comprising performing automatic seat contouring based on a user profile via an electronic processor and a seat adjustment subsystem.

[0197]

[0226] Example 38: The method of Example 22, To provide a user prompt to initiate interactive seat contouring via an electronic processor and output device, A method for further receiving via input devices and electronic processors.

[0198]

[0227] Example 39: The method of Example 22, The system determines whether or not an uncomfortable state exists via an electronic processor and multiple pressure sensors. A method further comprising recommending action to the user in response to the determination that an uncomfortable state exists.

[0199]

[0228] Example 40: A method of Example 22, wherein the seat includes multiple haptic feedback devices.

[0229] Example 41: A method of Example 40, wherein the treatment comprises one selected from the group consisting of seat contour adjustment, pneumatic massage, vibration massage, music massage, biometric massage, heart rate-based stress relief, interactive exercise, yoga, and thermal treatment.

[0200]

[0230] Example 42: The method of Example 41, Receiving treatment selections via input devices and electronic processors, A method further comprising performing a procedure via an electronic processor and a seat adjustment system.

[0201]

[0231] Example 43: A method relating to Example 42, further comprising recording discomfort states and treatments in a user profile.

[0232] Example 44: A method relating to Example 42, further comprising measuring the outcome of the procedure via a feedback device and an electronic processor.

[0202]

[0233] Example 45: A method for operating a seat, comprising a plurality of adjustable bladders located within the seat, a plurality of sensors positioned within the seat, a memory for storing user data and a seat adjustment program for controlling the plurality of adjustable bladders, and an electronic processor coupled to the memory, the plurality of adjustable bladders, and the plurality of sensors, wherein the electronic processor is configured to control the plurality of adjustable bladders according to the seat adjustment program, based on user data and feedback from at least one of the plurality of sensors, and this method is Receiving biometric signals about the user via multiple feedback devices and electronic processors, The system analyzes biometric signals via an electronic processor to determine the user's state, The electronic processor determines whether the user is in a negative state or not, A method comprising performing a biometric massage in response to determining that the user is in a negative state.

[0203]

[0234] Example 46: A method relating to Example 45, further comprising obtaining a biometric signal sample.

[0235] Example 47: A method of Example 46, wherein the biometric signal sample includes a signal related to the user's respiration or the user's heart rate.

[0204]

[0236] Example 48: The method of Example 46, further comprising filtering a biometric signal sample.

[0237] Example 49: The method of Example 48, further comprising changing the rate of a biometric signal sample to create a modified biometric signal sample.

[0205]

[0238] Example 50: A method of Example 48, further comprising activating at least one of a haptic feedback subsystem, a temperature subsystem, and an A / V feedback subsystem via an electronic processor to mimic a modified biometric signal sample and perform a biometric procedure.

[0206]

[0239] Example 51: The method of Example 50, further comprising activating at least one of the haptic feedback subsystem, the temperature subsystem, and the A / V feedback subsystem via an electronic processor to complement the simulated and modified biometric signal sample.

[0207]

[0240] Example 52: The method of Example 50, further comprising determining whether the user is still in a negative state via multiple feedback devices and an electronic processor.

[0208]

[0241] Example 53: A method of Example 50, further comprising assessing the success of a biometric procedure by comparing biological signals measured before, during, and after the procedure with target data via multiple feedback devices and an electronic processor.

[0209]

[0242] Example 54: A method relating to Example 52 or Example 53, further comprising further modifying the modified biometric signal sample.

[0243] Example 55: A method of Example 52 or Example 53, further comprising providing a user prompt via an output device and an electronic processor for stopping, continuing, or selecting a different type of action.

[0210]

[0244] Example 56: A method relating to Example 50, further comprising assessing the effect of the treatment on the user via a camera and an electronic processor.

[0245] Example 57: A method for operating a seat comprising a physiological sensor subsystem, a haptic feedback subsystem, a memory for storing user data and a seat adjustment program, and an electronic processor coupled to the memory, the physiological sensor subsystem, and the haptic feedback subsystem, wherein the electronic processor is configured to control the haptic feedback subsystem according to the seat adjustment program, and this method is The system receives user biometric data via a physiological sensor subsystem and an electronic processor, Receiving data from the user profile via memory and electronic processors, Determining the first heart rate value based on biometric data, The first heart rate value is compared to the user's standard heart rate value via an electronic processor, The first heart rate value and the standard heart rate value are determined to be similar within a predetermined threshold, When it is determined that the first heart rate value and the standard heart rate value are not similar, it is determined that the user's posture should be checked. Performing a Fourier transform on the first heart rate value generates the first transformation of the first heart rate value, Determining the first low-frequency value of the first transformation, Determining the first high-frequency value of the first conversion, To determine the ratio between a first low-frequency value and a first high-frequency value, A method comprising performing a procedure via an electronic processor and a haptic feedback subsystem.

[0211]

[0246] Example 58: A method of Example 57, wherein it is determined whether the ratio of low-frequency values ​​exceeds a predetermined value, and action is taken only if the allocated amount exceeds the predetermined value.

[0247] Example 59: A method of Example 57 or Example 58, further comprising performing a Fourier transform on a second first heart rate value to generate a second transform of the second heart rate value.

[0212]

[0248] Example 60: The method of Example 59, To determine the second low-frequency value of the second transformation, Determining the second high-frequency value of the second transformation, A method further comprising determining the ratio between a second low-frequency value and a second high-frequency value.

[0213]

[0249] Example 61: The method of Example 60, further comprising comparing the ratio of a first low-frequency value to a first high-frequency value with the ratio of a second low-frequency value to a second high-frequency value.

[0214]

[0250] Example 62: The method of Example 61, further comprising determining that the ratio of a first low-frequency value to a first high-frequency value and the ratio of a second low-frequency value to a second high-frequency value differ by a predetermined amount, and then displaying an indication of a change in the user's emotional state via a display device and an electronic processor.

[0215]

[0251] Example 63: The method of Example 62, further comprising displaying a user prompt via a display device and an electronic processor to initiate a new procedure, continue a procedure, or terminate a procedure.

[0216]

[0252] Example 64: A method for operating a seat for a seat user, the seat comprising a haptic feedback subsystem, a memory for storing user data and a seat adjustment program, and an electronic processor coupled to the memory, a physiological sensor subsystem, and the haptic feedback subsystem, wherein the electronic processor is configured to control the haptic feedback subsystem according to the seat adjustment program, and this method is The system receives user biometric data via a physiological sensor subsystem and an electronic processor, The user's state is determined via an electronic processor, In response to determining the user's state, the output device and electronic processor prompt the user to initiate a music-based massage. Prompting the user to select a mode associated with music that has a music signal via an output device and electronic processor, The haptic feedback system is activated in sync with the music and according to the selected mode to provide music-based massage. A method comprising prompting the user via an output device and an electronic processor whether or not to continue a music-based massage with different music.

[0217]

[0253] Example 65: A method relating to Example 64, further comprising assessing the effect that music-based massage has on a user via a camera and an electronic processor.

[0254] Example 66: A method of Example 64, further comprising assessing the effect of music-based massage on a user via a physiological sensor subsystem and an electronic processor.

[0218]

[0255] Example 67: The method of Example 64, further comprising filtering the musical signal before activating the haptic feedback system.

[0256] Example 68: A method for operating a seat configured to support a user, comprising a physiological sensor subsystem, a haptic feedback subsystem, a plurality of sensors, a memory for storing user data and a seat adjustment program, and an electronic processor coupled to the memory, the physiological sensor subsystem, and the haptic feedback subsystem, wherein the electronic processor is configured to control the haptic feedback subsystem according to the seat adjustment program, and this method is... The system receives user biometric data via a physiological sensor subsystem and an electronic processor, The user's state is determined via an electronic processor, In response to determining the user's state, the system prompts the user to begin an interactive exercise via an output device and an electronic processor. To provide interactive exercise prompts available for selection via output devices and electronic processors, The haptic feedback system is activated according to the selected interactive exercise, The output device and electronic processor prompt the user to choose whether or not to continue the music-based massage with different music, To activate interactive exercises via a haptic feedback system and electronic processor, Through multiple sensors and electronic processors, it is determined whether the user's movements match the sequence provided by the seat according to the interactive exercise, A method comprising outputting an indication that a user's movements do not match a sequence provided by a seat.

[0219]

[0257] Example 69: A method of Example 68, further comprising outputting a celebratory graphic if the user's movements match a sequence provided by the seat.

[0258] Example 70: The method of Example 68, further comprising prompting the user via an output device and an electronic processor to choose whether or not to continue the interactive exercise.

[0220]

[0259] Example 71: The method of Example 68, further comprising outputting the player's score via an output device and an electronic processor.

[0260] Example 72: A method of Example 68, further comprising assessing the effect that an interactive exercise has on a user via a camera and an electronic processor.

[0221]

[0261] Example 73: A method of Example 68, further comprising assessing the effect of interactive exercise on a user via a physiological sensor subsystem and an electronic processor.

[0222]

[0262] Example 74: A method of Example 68, wherein the interactive exercise is a dance simulator.

[0263] Example 75: The method of Example 68, The system determines the user's heart rate via a physiological sensor subsystem and an electronic processor, A method that further incorporates determining the difficulty level of interactive exercises based on heart rate.

[0223]

[0264] Example 76: The method of Example 68, where the interactive exercise is a game.

[0265] Example 77: A method relating to Example 76, further comprising selecting music for gameplay.

[0224]

[0266] Example 78: The method of Example 77, Determining a user's heart rate via a physiological sensor subsystem and an electronic processor, and further comprising determining a game-playing music based on the heart rate.

[0225]

[0267] Example 79: A method according to Example 76, further comprising displaying a pattern of shapes during game play.

[0268] Example 80: A method according to Example 79, further comprising determining, via a plurality of sensors and an electronic processor, whether a user's movement during game play matches a pattern of shapes.

[0226]

[0269] Example 81: A method according to Example 80, further comprising displaying a progress bar.

[0270] Example 82: A seat according to any one of Examples 1 to 16, further comprising a temperature subsystem.

[0227]

[0271] Example 83: A method according to any one of Examples 16 to 81, wherein the seat comprises a temperature subsystem.

[0272] Example 84: A method according to Example 83, further comprising determining the temperature of the seat via a temperature sensor, and adjusting the temperature of the seat via the temperature subsystem.

[0228]

[0273] Example 85: A seat comprising a frame, a plurality of seat cushions, a seat adjustment subsystem, a plurality of sensors disposed within the seat, a memory for storing user data and a seat adjustment program, A seat comprising a memory, a seat adjustment subsystem, and an electronic processor coupled to a plurality of sensors, the electronic processor being configured to control the seat adjustment subsystem based on user data and feedback from at least one of the plurality of sensors according to a seat adjustment program.

[0229]

[0274] Example 86: The seat of Example 85, further comprising a physiological sensor subsystem.

[0275] Example 87: The seat of Example 85 or Example 86, further comprising a haptic feedback subsystem.

[0230]

[0276] Example 88: The seat of Examples 85-87, further comprising a temperature subsystem.

[0277] Example 89: The seat of Examples 85-88, further comprising an audio / visual (A / V) feedback subsystem.

[0231]

[0278] Example 90: A seat comprising a frame, a plurality of seat cushions, a haptic feedback subsystem, a plurality of sensors disposed within the seat, a memory storing user data and a seat adjustment program, a memory, a haptic feedback subsystem, and an electronic processor coupled to the plurality of sensors, the electronic processor being configured to control the haptic feedback subsystem based on user data and feedback from at least one of the plurality of sensors according to a seat adjustment program.

[0232]

[0279] Example 91: The seat of Example 90, further comprising a physiological sensor subsystem.

[0280] Example 92: The seat of Example 90 or Example 91, further comprising a seat adjustment subsystem. ]

[0233]

[0281] Example 93: A seat according to Examples 90 to 92, further comprising a temperature subsystem 236.

[0282] Example 94: A seat according to Examples 90-93, further comprising an audio / visual (A / V) feedback subsystem.

[0234]

[0283] Example 95: A method for automatic seat adjustment by the process discussed herein.

[0284] The above specification describes specific embodiments. However, those skilled in the art will recognize that various modifications and variations can be made without departing from the scope of the invention as described in the following claims. Accordingly, the specification and drawings should be considered illustrative rather than restrictive, and all such modifications are included within the scope of this teaching.

[0235]

[0285] No advantage, merit, solution to a problem, or any element that brings to mind or makes more apparent an advantage, merit, or solution should be construed as an important, essential, or indispensable feature or element of any part or all of the claims. The present invention is defined solely by the appended claims, including all amendments made during the pendency of this application and all equivalents of those claims issued.

[0236]

[0286] Furthermore, in this text, relational terms such as first and second, upper and lower are used solely to distinguish one entity or action from another entity or action, and do not necessarily require or imply any actual relationship or order between such entities or actions. "Equip," "equip," "have," "contain," "include," "contain," "include," or any other variation thereof are intended to cover non-exclusive inclusion, and a process, method, article, or apparatus that equips, equips, equips, includes, or contains a list of elements may include not only those elements but also other elements not expressly listed or specific to such process, method, article, or apparatus. Elements beginning with "equip," "have," "include," or "contain" do not, unless further constraints, exclude the presence of additional identical elements in a process, method, article, or apparatus that equips, equips, has, equips, or contains that element. The terms "a" and "an" are defined as one or more unless expressly otherwise stated. The terms “substantially,” “essentially,” “approximately,” “about,” and “about,” or other versions thereof, are defined as “as well as understood by those skilled in the art,” and in one non-limiting embodiment, the term is defined as “within 10%, in another embodiment within 5%, in yet another embodiment within 1%, and in yet another embodiment within 0.5%. As used herein, the term “combined” is defined as being connected, but not necessarily directly or mechanically. A device or structure “configured” in a particular way is configured in at least that way, but may also be configured in ways not listed.

[0237]

[0287] The disclosure summary is provided to allow readers to quickly confirm the nature of the technical disclosure. The summary is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, it will be seen that in the detailed description above, various features are grouped into various embodiments for the purpose of simplifying the disclosure. This method of disclosure should not be interpreted as reflecting an intention that the claimed embodiments require more features than expressly described in each claim. Rather, as reflected in the following claims, the subject matter of the invention is fewer than all the features of a single disclosed embodiment. Accordingly, the following claims are incorporated into the detailed description, and each claim stands alone as separately claimed subject matter.

Claims

1. A seat, Frame and, Multiple seat cushions, Multiple adjustable bladders located within the aforementioned seat, Multiple sensors arranged within the aforementioned seat, A plurality of voice coils arranged within the seat, each voice coil being associated on a one-to-one basis with one of the plurality of adjustable bladders, A memory for storing user data and multiple seat adjustment programs for controlling the multiple adjustable bladders and the multiple voice coils, An electronic processor coupled to the memory, the plurality of adjustable bladders, the plurality of voice coils, and the plurality of sensors, the electronic processor configured to control the plurality of adjustable bladders and the plurality of voice coils according to the seat adjustment program and based on the user data and feedback from at least one of the plurality of sensors. Equipped with, The plurality of adjustable bladders, the plurality of voice coils, or both of the plurality of adjustable bladders and the plurality of voice coils are configured to provide a massage output. The seat further comprises a plurality of temperature control elements configured to complement the massage output by adjusting the temperature of the seat according to massage parameters. seat.

2. A seat according to claim 1, wherein the plurality of seat cushions include a seat base cushion, a backrest cushion, and a headrest cushion.

3. A seat according to claim 1, wherein the plurality of temperature control elements are configured to provide heat to warm the user of the seat before the user begins an activity associated with the massage output.

4. A seat according to claim 1, wherein the plurality of temperature control elements are configured to cool the user of the seat after the user has completed an activity associated with the massage output.

5. A seat according to claim 1, wherein the plurality of sensors include physiological sensors configured to measure a biometric signal, the biometric signal includes at least one of heart rate, heart rate variability (HRV), and respiratory rate. The massage output includes a biometric massage treatment configured to mimic the biometric signal and then be modified to output according to the modified biometric signal, wherein the modified biometric signal is adjusted based on the user's state determined based on the biometric signal. seat.

6. A seat according to claim 1, wherein the plurality of seat adjustment programs include static comfort modules, and the electronic processor is configured to establish the contour of the seat.

7. The seat according to claim 6, wherein the electronic processor is The seat contour is established via the seat adjustment subsystem based on the user's size, shape, and personal preferences. A seat configured in such a way.

8. A seat according to claim 7, wherein establishing the contour of the seat via a seat adjustment subsystem includes adjusting a combination of a bolster, a lumbar support, the plurality of adjustable bladders, seat recline, seat height, and seat angle.

9. A seat according to claim 8, wherein the electronic processor is configured to assess the pressure between the user and the seat.

10. A seat according to claim 9, wherein the electronic processor is configured to determine the total load measured by a plurality of pressure sensors before assessing the pressure between the user and the seat.

11. A seat according to claim 6, wherein the plurality of sensors include a plurality of pressure sensors arranged in a plurality of locations, and the electronic processor is configured to generate a map of pressure values ​​based on the pressures sensed by the plurality of pressure sensors.

12. A seat according to claim 11, wherein the map of pressure values ​​is stored in a user profile.

13. A seat according to claim 11, wherein the pressure values ​​are overlaid on a pressure grid representing local body mapping zones of a human body model.

14. The seat according to claim 6, wherein the electronic processor is The pressure scan of the aforementioned seat is controlled to establish an initial baseline pressure, The initial contour static comfort configuration of the seat is established via the seat adjustment subsystem. A seat configured in such a way.

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