Intervention based on the detected gait kinematics

Abstract

A system that provides an intervention based on the detection of gait kinematics for treatment, training, gaming, or mobility assistance. This system includes a footwear incorporating at least one sensor, a data processor, and a wireless communication unit, and a remote intervention system configured to provide an intervention for eliciting a response from a subject wearing the footwear. The sensor is configured to generate sensor data related to the movements of the subject. The data processor is configured to process the sensor data to generate gait parameter data related to the gait kinematics of the subject, and the wireless communication unit is configured to communicate the gait parameter data to the remote intervention system.

Description

Technical Field

[0001] The present disclosure relates to providing an intervention based on detected gait kinematics for therapy, training, gaming, or mobility assistance.

Background Art

[0002] Techniques for stimulating the human foot with vibrations for therapeutic reasons are known in the art (see, for example, "Subsensory vibrations to the feet reduce gait variability in elderly fallers", Galica et al).

[0003] Typically, these techniques monitor specific aspects of a subject's walking motion to recognize the movements to which vibration stimulation should be applied, and then apply appropriate vibrations.

[0004] These techniques are often used in a research laboratory for motion analysis. However, systems that can also be used outside the laboratory have been proposed.

[0005] For example, International Publication No. 2017 / 023864 proposes a system that modifies a subject's walking motion by applying electrical or vibrotactile stimulation to the subject's feet to assist with osteoarthritis.

Prior Art Documents

Non-Patent Documents

[0006]

Non-Patent Document 1

Patent Documents

[0007]

Patent Document 1

SUMMARY OF THE INVENTION

[0008] According to a first aspect of the present disclosure, there is provided a system for providing an intervention based on detected walking kinematics for therapy, training, gaming, or mobility assistance, the system comprising at least one footwear incorporating one or more sensors, a data processor, and a wireless communication unit, and a remote intervention system configured to provide an intervention that elicits a response from a subject wearing the footwear. The one or more sensors are configured to generate sensor data related to the movement of the subject, the data processor is configured to process the sensor data to generate walking parameter data related to the walking kinematics of the subject, and the wireless communication unit is configured to communicate the walking parameter data to the remote intervention system.

[0009] Further, the remote intervention system is configured to provide a sensory intervention.

[0010] Further, the remote intervention system includes at least one stimulation device such as a spinal cord stimulation device, a deep brain stimulation device, or a muscle stimulation device.

[0011] Further, the remote intervention system includes a simulator such as a virtual reality system or an augmented reality system.

[0012] Further, at least one of the footwear further includes a memory configured to store sensor data and / or walking parameter data.

[0013] Further, the data processor is configured to compare the sensor data and / or walking parameter data with stored sensor data and / or walking parameter data to determine whether the sensor data and / or walking parameter data correspond to a walking event.

[0014] Further, when it is determined that the sensor data and / or the walking parameter data correspond to a walking event, the data processor is configured to control the wireless communication unit to communicate the walking parameter data to the remote intervention system.

[0015] Further, the walking event is at least any one of the following: a situation where there is an imminent risk of falling or a high risk of falling for the subject, a situation where there is an imminent risk of stopping walking or a high risk of tripping for the subject, a deviation from a desired movement for the subject, and a maintenance of the form of a desired movement for the subject.

[0016] Also, the data processor is configured to periodically generate walking parameter data at a predetermined interval and store the generated walking parameter data in a memory. The predetermined interval may be an interval suitable for the determined walking parameters. For example, walking parameter data (such as walking stability) that can be determined without requiring the completion of a full stride / walk may be periodically generated at a predetermined interval shorter than the human reaction time. For example, the interval may be less than 0.1 second. Walking parameter data that requires the completion of a full step / stride (such as stride length) is generated at a predetermined interval that is not less than the duration of the subject's step / stride (pace) or not less than the duration of a typical human stride / stride (human walking rhythm) for performing a specific movement, for example, an interval of 0.5 second or more and 2 seconds or less, for example, a predetermined interval of 1 second.

[0017] Also, the walking parameter data includes data related to walking speed, step / stride speed, step / stride length, variation in swing time, stride length, stride duration, step / stride width, rhythm, variation, asymmetry, posture control, step characteristics, pace, walking speed, swing - stance - ratio, heel - off, toe - off, heel - strike, flat - foot contact, variation in walking, and walking stability.

[0018] Also, one or more sensors, a data processor, a memory, and a wireless communication unit are embedded in the sole or insole of the footwear.

[0019] Also, the sensor has one or more inertial measurement devices including one or more of an accelerometer, a gyroscope, and a magnetometer.

[0020] Also, the sensor further includes one or more of a plantar pressure sensor for detecting a pressure change caused by the subject's contact with the ground, a temperature sensor for detecting the ambient temperature, a barometric pressure sensor for detecting the barometric pressure, and a sound sensor.

[0021] Also, the at least one footwear further incorporates movement distance tracking means configured to generate movement distance data related to the distance the footwear has moved, and the data processor is configured to process the movement distance data to generate movement distance analysis data.

[0022] Also, the wireless communication unit is configured to communicate the movement distance analysis data to the remote intervention system.

[0023] Also, the at least one footwear has a rechargeable battery for supplying power to components incorporated therein.

[0024] A second aspect of the intervention of the present disclosure provides a method of providing an intervention based on detected gait kinematics for therapy, training, gaming, or mobility assistance, the method comprising, in a footwear, generating sensor data related to the movement of a subject wearing the footwear, processing the sensor data of the footwear to generate gait parameter data related to the gait movement of the subject, communicating the gait parameter data from the footwear to a remote intervention system to provide an intervention, and controlling the remote intervention system to provide an intervention that elicits a response from the subject wearing the footwear.

[0025] In a third aspect of the intervention of the present disclosure, an arrangement for attachment to footwear is provided, the arrangement including one or more sensors, a data processor, and a wireless communication unit, the one or more sensors being configured to generate sensor data related to the movement of a subject wearing the footwear, the data processor being configured to process the sensor data to generate gait parameter data related to the gait kinematics of the subject, and the wireless communication unit being configured to communicate the gait parameter data to a remote intervention system.

[0026] In a fourth aspect of the intervention of the present disclosure, footwear having attached thereto the arrangement according to the third aspect of the intervention of the present disclosure is provided.

[0027] In a fifth aspect of the intervention of the present disclosure, a pair of footwear is provided having a left-foot footwear according to the fourth aspect of the intervention of the present disclosure and a right-foot footwear according to the fourth aspect of the intervention of the present disclosure.

[0028] In a sixth aspect of the intervention of the present disclosure, a computer program is provided for execution on a data processor incorporated in a part of the footwear and for use in the system according to the first aspect of the intervention of the present disclosure, the computer program including instructions which, when executed on the data processor, cause the data processor to control the generation of sensor data related to the movement of the wearer of the footwear in the footwear, process the sensor data in the footwear to generate gait parameter data related to the gait kinematics of the wearer, and perform operations including communicating the gait parameter data from the footwear to a remote intervention system to provide an intervention for inducing a response by the wearer of the footwear.

[0029] According to an embodiment of the intervention of the present disclosure, a system for providing an intervention is provided, the system comprising an optimized system architecture for treatment, training, gaming, or mobility assistance based on detected gait kinematics.

[0030] According to embodiments of the present disclosure, data regarding a subject can be collected outside of a clinical environment, for example, in a familiar environment with unbiased conditions, which is likely to lead to better analysis and related therapies. According to embodiments of the present disclosure, a subject's walking can be analyzed in a quantitative, objective, and reproducible manner. In some applications, a therapist can, for example, determine objectively and without bias whether a patient's symptoms have improved.

[0031] Other features and aspects of the present disclosure are defined in the claims.

Brief Description of the Drawings

[0032] Hereinafter, embodiments of the present disclosure will be described by way of example only with reference to the accompanying drawings. Corresponding reference numerals are assigned to similar parts.

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DETAILED DESCRIPTION OF THE INVENTION

[0033] FIG. 1a is a schematic diagram of a system that provides an intervention based on detected walking kinematics, and includes a pair of footwear 101 and a network deployment N.

[0034] The footwear 101 has a pair of footwear provided by a pair of shoes 101 including a first shoe 101a and a second shoe 101b. Usually, the first shoe 101a and the second shoe 101b are the same except that they are configured to fit the right foot and the left foot of the subject, respectively.

[0035] The sole 102 of each shoe 101a, 101b has a cavity 103, and a sensor module 104 is attached inside the cavity.

[0036] As shown in FIG. 1b, the sensor module 104 includes a power supply unit 105, a wireless communication unit 106, a data processor 107a and a corresponding memory unit 107b, an optional vibration actuator 108, and a sensor unit 109 having a plurality of sensors.

[0037] The power supply unit 105 may be provided by a suitable rechargeable battery well-known in the art. The battery may be charged by any suitable means, such as a suitable power cable input interface or an induction coil incorporated in a power source for wireless charging.

[0038] The network deployment N has a data network 110a and a radio base station 111, and is configured such that the sensor module 104 transmits data or receives data from the remote intervention system 112 via the radio base station 111.

[0039] The remote intervention system 112 may include at least one or more electrical stimulation devices such as a deep brain stimulation device or a spinal cord stimulation device configured to stimulate a part away from the foot area of the subject.

[0040] Alternatively, or in addition, the remote intervention system 112 may include a simulator such as a virtual reality system that provides a metaverse and / or an augmented reality system having a screen capable of displaying an image of a video of the subject and / or a simulation of the subject. The image can be augmented with visual information such as visual information of the metaverse or graphics that give visual clues to the subject.

[0041] Generally, an intervention is considered to be any form of feedback to a subject wearing the footwear 101 or a third party such as a clinician to cause a reaction by the subject to the intervention in a desirable way, in the sense described in the claims. The intervention can be, for example, an electrical stimulation, a tactile intervention, a visual intervention such as an image on a display screen, or a sensory intervention such as an audible intervention. In the embodiments described herein, a remote intervention is an intervention away from the area of the foot or feet of the subject on whom the footwear is worn.

[0042] In an embodiment, the data network 110a can be provided by any suitable network for transmitting data between computing devices, such as the Internet. The radio base station 111 is compatible with the wireless communication unit 106 and can be provided by any suitable wireless access point suitable for communicating data to and receiving data from the data network 110a, such as a properly connected Wi-Fi router. In an alternative embodiment, the radio base station 111 can be provided by a smartphone, a similar mobile device, a tablet, or any other device with suitable communication capabilities.

[0043] In use, for each sensor module 104 within each shoe, the plurality of sensors of the sensor unit 109 are configured to detect the movement of the subject when wearing the shoe and generate corresponding sensor data related to this movement. Generally, the sensor data includes at least one or more linear acceleration data (generated by an accelerometer), angular velocity data (generated by a gyroscope), and orientation data (generated by a magnetometer).

[0044] The data processor 107a processes this sensor data to generate gait parameter data related to the gait kinematics of the subject. For example, as shown in FIG. 3, the data processor 107a processes the sensor data from the sensor modules of each shoe 101a, 101b to execute a gait characterization function 113 configured to characterize aspects of the gait kinematics of the subject.

[0045] The walking feature extraction function 113 implements one or more walking feature quantity algorithms that receive sensor data and generate walking parameter data related to the walking of the subject derivable from the sensor data. Techniques for converting such sensor data into walking parameter data are well known. For example, it is well known to identify "walking events" such as toe-off and heel strike using peaks, valleys, zero crossings, etc. in sensor data generated by sensors that monitor human movement.

[0046] The walking feature extraction algorithm or the walking parameter data generated by the walking feature extraction algorithm may include data related to any one or a combination of walking speed, step speed, stride, variation in walking cycle, stride length, step width, rhythm (such as step time, swing time, stance time, single-leg support time, double-leg support time, etc.), variation (such as variation in step speed, variation in step length, variation in step time, variation in stance time, etc.), asymmetry (such as swing time asymmetry, step time asymmetry, stance time asymmetry, etc.), posture control (such as stride length asymmetry, etc.), step characteristics (landing angle, minimum toe clearance, foot angle (such as adduction angle, landing angle, lift-off angle, angular velocity, etc.), peak parameters (such as peak propulsion force, peak braking force, etc.), force / pressure values and power, etc.). The walking parameters may further include one or more of load intensity and period, and pressure distribution.

[0047] The walking parameter data is transmitted from the wireless communication unit 106 to the remote intervention system 112 via the wireless base station 111 and the data network 110a.

[0048] The remote intervention system 112 may be further configured to receive program parameters specified by a treatment program, an operation assistance program, a game program, or a training program from a program parameter database 117 connected to the remote intervention system 112. These program parameters quantify how aspects of the subject's walking kinetics change from normal movement when intervention is required.

[0049] Using one of the walking parameters, a combination of walking parameters, or all of the walking parameters, and one or more program parameters specified by a treatment program, an action assistance program, a game program, or a training program, the remote intervention system 112 is configured to determine an appropriate intervention according to the parameters specified by the treatment program, the action assistance program, the game program, or the training program.

[0050] For example, when the remote intervention system 112 has an electrical stimulation device, such as a deep brain stimulation device or a spinal cord stimulation device, the intervention system 112 gives an appropriate stimulus to the subject so that the subject responds in a desired manner.

[0051] Alternatively, or in addition thereto, the data processor 107a is configured to determine whether the determined walking parameter indicates a walking event. For example, as shown in FIG. 3, the data processor 107a is configured to execute a walking event prediction function 114 and determine whether the determined walking parameter corresponds to a walking event that deviates from a desired motion such as an imminent fall or a catching foot.

[0052] When a walking event is determined, the data processor 107a controls the wireless communication unit 106 to communicate the walking parameter data associated with the walking event to the remote intervention system 112.

[0053] For example, the walking event prediction function 114 may determine moving average data or moving variance data of one or more walking parameters from the walking parameter data stored in the memory unit 107b. For example, the data processor 107a may be configured to periodically generate walking parameter data at a predetermined interval and store the generated walking parameter data in the memory unit 107b. The predetermined interval may be an interval suitable for the walking parameters to be determined. For example, walking parameter data (e.g., walking stability) that can be determined without requiring the completion of a full stride / walk may be periodically generated at a predetermined interval shorter than the human reaction time. For example, the interval may be less than 0.1 second. Walking parameter data that requires the completion of a full stride / walk (such as stride length) is generated at a predetermined interval that is not less than the duration of the subject's stride / walk (pace), or at a predetermined interval that is not less than the duration of the typical stride / stride (human walking rhythm) of a human performing a specific action, for example, not less than 0.5 second and not more than 2 seconds, for example, a predetermined interval of 1 second.

[0054] By comparing the walking parameters with the moving average or moving variance, it is possible to determine whether a walking event has occurred. If a walking event has occurred, the walking parameter data corresponding to the walking event is transmitted to the remote intervention system 112 in order to perform an appropriate intervention.

[0055] Furthermore, the data processor 107a can control the vibration actuator 108 to apply an appropriate stimulus to the subject's foot based on the determined walking parameters. When the intervention, particularly the intervention by stimulation, is provided by the remote intervention system 112, the stimulation by the vibration actuator 108 may not be necessary. Usually, the vibration is transmitted to the subject's foot through the middle part of the sole between the vibration actuator 108 and the subject's foot.

[0056] As an example, the system can be used in a fall prevention support program to generate appropriate warning signals for reducing the possibility of falls for the elderly and other vulnerable subjects.

[0057] During use, the subject wears the shoes and walks, and corresponding sensor data is generated by the sensors.

[0058] The gait characterization function 113 uses this sensor data to generate gait parameter data related to the timing of the pendulum of the gait (i.e., the time it takes for the subject to complete a step) when the subject walks.

[0059] The subject's swing time can usually be reliably obtained with a simple algorithm. The swing time parameter can be generated by the gait characterization function 113 identifying the time lag between "toe-off" and "heel-strike" of each foot from the sensor data.

[0060] Specifically, from the sensor data, the gait characterization function 113 is configured to detect toe-off and heel-strike events by applying a peak detection algorithm to the sensor data related to the angular rate of the ankle.

[0061] The sensor data related to a step usually shows two peaks in the vicinity of toe-off and heel-strike. By combining this information with the sensor data related to the vertical acceleration (lift-off at toe-off and impact at heel-strike), it becomes possible to estimate and generate toe-off and heel-strike events in real time.

[0062] The gait characterization function 113 is configured to generate swing time data (i.e., gait parameter data). The swing time data is then transmitted by the wireless communication unit 106 to the remote intervention system 112.

[0063] In response to the received swing data, the remote intervention system 112 performs an appropriate intervention. For example, the remote intervention system 112 can compare the received swing time data with the swing time data stored in the program parameter database 117, such as the swing time data corresponding to the subject's normal movement, to determine that a fall is imminent.

[0064] When the remote intervention system 112 has an electrical stimulation device, such as a deep brain stimulation device or a spinal cord stimulation device, the remote intervention system 112 generates a sensory stimulus warning the subject of the risk of falling and / or stimulates the subject's body to perform appropriate actions to prevent falling.

[0065] Alternatively, or in addition thereto, the gait characterization function 113 is configured to identify a number of toe-off and heel-strike events from the sensor data and generate a plurality of swing time values.

[0066] And the gait characterization function 113 is configured to generate an average swing time value, which is the average of the plurality of swing time values, from the plurality of swing time values.

[0067] The gait characterization function 113 is further configured to calculate, using the plurality of swing time values, a time value corresponding to one standard deviation from this average swing time value of the plurality of swing time values. The plurality of swing time values, the average swing time value, and the standard deviation of the swing time values may be stored in the memory unit 107b.

[0068] The data processor 107a executes a gait event prediction function 114 configured to process the swing time gait parameter data generated by the gait characterization function 113 and determine whether the gait parameter data indicates an imminent fall. For example, the gait event prediction function 114 may be configured to determine whether the determined swing time data is within a predetermined number of standard deviations from the average swing time of the subject, whereby the swing time of the subject increases when a fall is predicted to be imminent.

[0069] For example, the walking characterization function 113 may calculate from the sensor data that the average swing time of the subject is 700 milliseconds and the distribution of the swing time is such that one standard deviation from the average swing time is 250 milliseconds. Therefore, the walking parameter data transmitted from the walking characterization function 113 to the walking event prediction function 114 specifies the average swing time value of 700 milliseconds and a value corresponding to one standard deviation of the standard deviation time value of 250 milliseconds.

[0070] Furthermore, the program parameter database 117 may include program parameter data indicating that when the swing time of the subject increases beyond the threshold by two deviations from the average swing time, it is a sign of an impending fall.

[0071] Therefore, in this example, the walking swing time is at least as follows. 700 milliseconds + (2 × 250 milliseconds) = 1200 milliseconds

[0072] In such an example, the walking event prediction function 114 is configured to determine that a fall is impending if the swing time of the subject becomes 1200 milliseconds or more.

[0073] Therefore, when the walking swing time of the subject changes to exceed 1200 milliseconds, the data processor 107a identifies that the determined swing time exceeds the walking swing time threshold and communicates the swing time (i.e., the walking parameter data) to the remote intervention system 112 via the wireless communication unit 106.

[0074] In response to the received swing time data, the remote intervention system 112 performs appropriate intervention. For example, if the remote intervention system 112 has an electrical stimulation device such as a deep brain stimulation device or a spinal cord stimulation device, the remote intervention system 112 generates a sensory stimulus to warn the subject that the subject is likely to fall and / or stimulates the subject's body to perform appropriate actions to prevent the fall.

[0075] The data processor 107a generates corresponding control signals, and when these control signals are received by the vibration actuator 108, the vibration actuator 108 generates corresponding sensory stimuli that warn the subject of the risk of falling. The subject thus warned is less likely to fall.

[0076] The detection of sensor data related to the swing time by the data processor 107a is usually performed at a speed faster than the human reaction time. Thus, intervention is started immediately when the set threshold is exceeded, and the subject experiences smooth and "instantaneous" feedback. Usually, the human reaction time is about 0.1 seconds, and when the subject's walking swing time is detected at 100 Hz, smooth operation is achieved.

[0077] In another example, the system can be used in a therapy program to assist subjects suffering from neurological diseases such as multiple sclerosis and Parkinson's disease and experiencing "stiff feet".

[0078] In such an example, as in the previous example, the subject walks wearing the shoes, and corresponding sensor data is generated by the sensors.

[0079] The gait characterization function 113 uses this sensor data to generate gait parameter data including gait parameter data related to the gait swing time during normal walking of the subject, as in the previous example.

[0080] The gait characterization function 113 is configured to generate swing time data (i.e., gait parameter data). Then, the swing time data is transmitted to the remote intervention system 112 by the wireless communication unit 106.

[0081] In response to the received swing data, the remote intervention system 112 provides appropriate intervention. For example, the remote intervention system 112 compares the received swing time data with the swing time data stored in the program parameter database 117, such as swing time data correlated with an impending trip hazard such as a predetermined decrease (e.g., 50%) or more in the average swing time over a predetermined period (e.g., 60 seconds), to determine an impending trip hazard.

[0082] When the remote intervention system 112 has an electrical stimulation device, such as a deep brain stimulation device or a spinal cord stimulation device, the remote intervention system 112 generates a sensory stimulus warning the subject of the risk of falling and / or stimulates the subject's body to make appropriate movements to prevent a trip hazard.

[0083] Alternatively, or in addition thereto, the memory device 107b stores program parameters designating that a decrease of a predetermined amount (e.g., 50%) or more in the average swing time over a predetermined period (e.g., 60 seconds) is a sign of an impending trip hazard. If the subject's average swing time decreases by at least the threshold amount (e.g., at least 50%) during a threshold period (e.g., 60 seconds) indicating symptoms of an impending trip hazard, the walking event prediction function 114 generates "trip hazard" impending walking parameter event data and transmits the data to the remote intervention system 112.

[0084] In response to the received "trip hazard" impending walking parameter event data, the intervention system 112 performs appropriate intervention. For example, when the intervention system 112 includes an electrical stimulation device such as a deep brain stimulation device or a spinal cord stimulation device, the intervention system 112 generates a sensory stimulus warning that the subject may be afflicted with symptoms of a trip hazard and / or stimulates the subject's body to make appropriate movements to prevent the symptoms of a trip hazard.

[0085] The data processor 107a can also generate corresponding control signals. When these control signals are received by the vibration actuator 108, the vibration actuator 108 generates corresponding sensory stimuli, warns the subject to start walking and eliminate the cramped foot, so that the subject who is warned in this way is less likely to be troubled by the symptoms of the cramped foot.

[0086] In another example, the system can be used in a training program to assist a subject who aims to improve their skills when performing activities such as running.

[0087] In such an example, similar to the previous example, the subject wears shoes and moves around, especially in a specific desired movement form. The corresponding sensor data is generated by the sensor.

[0088] The gait characterization function 113 uses this sensor data to generate gait parameter data indicating one or more gait parameters related to the desired movement pattern, such as gait length and swing time.

[0089] The gait characterization function 113 is configured to generate swing time data and gait length data (i.e., gait parameter data). The swing time data and gait length data are then transmitted to the remote intervention system 112 via the wireless communication unit 106.

[0090] In response to the received swing time data and gait length data, the remote intervention system 112 performs appropriate intervention. For example, the remote intervention system 112 may compare the received swing time data and gait length data with the swing time data and gait length data stored in the program parameter database 117 to identify a change in swing time and gait length of 5% or more compared to that specified in the motion training program stored in the program parameter database 117.

[0091] The remote intervention system 112 has an electrical stimulation device such as a deep brain stimulation device, a spinal cord stimulation device, or a muscle stimulation device. The remote intervention system 112 generates a sensory stimulus to warn the subject that the movement of the subject has deviated from the desired form and / or to stimulate the subject's body to perform an appropriate movement to correct the deviation.

[0092] Alternatively, or in addition thereto, the storage device 107b stores program parameters related to an exercise training program that specifies swing time data and step width data parameters. These parameters are compared with the received swing time data and step width data. When the received swing time data and step width data of the subject deviate by 5% or more from those specified in the exercise training program, indicating a deviation from the desired movement form, the walking event prediction function 114 generates form deviation walking event data and transmits it to the remote intervention system 112.

[0093] In response to the received form deviation walking event data, the intervention system 112 provides an appropriate intervention. The intervention system 112 has an electrical stimulation device such as a deep brain stimulation device or a spinal cord stimulation device. The intervention system 112 warns the subject that the subject has deviated from the desired form and / or generates a sensory stimulus to stimulate the subject's body to perform an appropriate corrective movement.

[0094] The data processor 107a can also generate a corresponding control signal. When this control signal is received by the vibration actuator 108, the vibration actuator 108 generates a corresponding sensory stimulus to warn the subject to perform an appropriate corrective movement.

[0095] However, in some cases, when a form deviation walking event is communicated to the remote intervention system 112, the remote intervention system 112 stops the intervention application. For example, the remote intervention system 112 may be configured according to a training program that provides regular intervention to inform the subject (e.g., an athlete) that they are moving at a desired pace. When it is determined that the subject has fallen below or exceeded this pace, walking event data deviating from the corresponding pace is generated and communicated to the remote intervention system 112, and then the provision of regular intervention is stopped until the desired pace is achieved again.

[0096] As a further example, the remote intervention system 112 may include an augmented reality (AR) system in which an image of the real-world environment is augmented by computer-generated sensory stimuli (e.g., visual stimuli such as images, audible stimuli, or tactile stimuli), or a virtual reality (VR) system in which a virtual world is simulated. The AR system may include virtual objects spatially registered within an image of the real-world environment. The virtual reality (VR) system may include a simulation in which the subject is represented, such as a metaverse. In this context, the intervention provided by the remote intervention system having an AR / VR system is any sensory stimulus that a person, particularly the subject, can experience.

[0097] In a particular system that can be used in a training program to assist a subject aiming to improve their technique when performing activities such as running, the remote intervention system 112 includes an augmented reality (AR) system or a virtual reality (VR) system.

[0098] The gait characterization function 113 generates gait parameter data indicating one or more gait parameters related to a desired motion pattern using sensor data acquired while the subject is walking around wearing shoes.

[0099] The walking parameter data is transmitted by the data processor 107a to the remote intervention system 112 via the wireless communication unit 106. The walking parameter data is then processed by the remote intervention system 112 to provide an intervention in the form of sensory feedback such as visual feedback, to which the subject responds. For example, the visual feedback may be a virtual target displayed in front of the subject (or a representation of the subject) on the display of the AR / VR system, and the subject is instructed to follow it. If it is determined that the subject's walking speed is too slow, the virtual target can be moved away from the subject within the AR / VR system to prompt the subject to increase the walking speed. Alternatively, or in addition thereto, the visual feedback is provided by modifying the virtual environment according to a pre-set training program. For example, the subject's walking can be reproduced within a virtual reality system such as the metaverse.

[0100] The program parameters stored in the program parameter database 117 or the memory unit 107b are defined based on the type of program provided (e.g., training program, therapy program, game program, or motion assistance program). In any case, the program parameters may be selected based on relevant research. For example, some of the program parameters of a therapy program that attempts to reduce or decrease the occurrence of toe-in are defined based on research suggesting its effectiveness in treating this symptom.

[0101] The program parameters can be partially defined by past data related to the subject. For example, a particular subject may have shown a certain sequence of walking kinematics before the occurrence of toe-in symptoms. In such an example, the program parameters can be selected to identify these walking kinematics.

[0102] Figure 2 provides a schematic diagram summarizing one of the operating modes of the above-described system.

[0103] In the first stage S201, sensor data is generated by sensors of at least one of a pair of shoes.

[0104] In the second stage S202, the walking characterization function 113 processes the sensor data and generates walking parameter data related to the walking kinematics of the subject.

[0105] In the third stage S203, the walking event prediction function 114 determines whether the walking parameter data indicates a walking event. If the walking parameter data indicates a walking event, the walking parameter data is communicated to the remote intervention system.

[0106] In the fourth stage S204, in response to receiving the walking parameter data, the remote intervention system generates an intervention and the subject responds thereto.

[0107] This means that a training program, an operation assistance program, or a therapy program can continue to effectively adapt even if the walking kinetics of the subject changes over time due to changes by, for example, a training program or a therapy program.

[0108] FIG. 3 is a schematic diagram showing a more detailed view of the sensor module 104 arranged according to some embodiments of the present disclosure.

[0109] As shown, in some embodiments, the sensor module 104 has a power supply unit 105 including one or more rechargeable batteries 105a and an inductive charging loop 105b for charging the rechargeable battery 105a via a wireless charging unit.

[0110] The sensor module 104 further includes a data processor 107a provided by any suitable programmable microprocessor or other suitable data processing means, such as a custom-designed integrated circuit such as a field programmable gate array (FPGA).

[0111] The data processor 107a is connected to the motor output control circuit via suitable signal lines, and is further connected to the vibration actuator 108 via suitable signal lines.

[0112] The vibration actuator is typically provided by an electric motor composed of a weight eccentrically mounted on the shaft of the motor. However, the vibration actuator may be provided by other suitable electromechanical devices, such as a piezoelectric vibration actuator or a linear electromagnetic actuator (a "tactuator") such as a voice coil.

[0113] The sensor unit 109 is connected to the data processor 107a via suitable signal lines. The sensor unit 109 is typically provided by an inertial measurement unit (IMU) having an accelerometer, a gyroscope, and a magnetometer connected to the data processor unit.

[0114] The wireless communication unit 106 is also connected to the data processor 107a via suitable signal lines. The wireless communication unit 106 can be provided by any suitable wireless communication unit operating according to conventional wireless protocols such as Bluetooth, Zigbee, LoRa, NFC, WiFi, etc. In some examples, the wireless communication unit 106 may be provided by a data transmitter, receiver, and / or transceiver that includes a subscriber identity module (SIM) and enables data transmission and reception with the data network 110a via a cellular mobile phone network.

[0115] All components of the sensor module 104 are connected to the power supply unit 105 via suitable power lines.

[0116] FIG. 4 is a schematic diagram showing in more detail the sensors of the sensor unit 109 in some embodiments. As can be seen from FIG. 4, the sensor unit 109 has an accelerometer 401, a gyroscope 402, and a magnetometer 403. This combination of sensors typically provides information sufficient to reveal the walking speed, cadence speed, stride, swing time variability, stride length, step, rhythm (cadence time, swing time, stance time, single-leg support, double-leg support, etc.), variability (cadence speed variability, stride variability, cadence time variability, stance time variability, etc.), asymmetry (swing time asymmetry, cadence time asymmetry, stance time asymmetry, etc.), posture control (stride asymmetry, etc.), walking characteristics (landing angle, minimum toe clearance, foot angle, etc.), asymmetry (swing time asymmetry, step time asymmetry, stance time asymmetry, etc.), posture control (step length asymmetry, etc.), step characteristics (landing angle, minimum toe clearance, foot angle (eversion angle, landing angle, lift-off angle, angular velocity, etc.), peak parameters (peak propulsion force, peak brake, etc.)) of the subject's movement.

[0117] In some embodiments, the sensor unit 109 may include one or more additional sensors.

[0118] FIG. 5 is a schematic diagram showing a further example of a sensor unit 501 that further includes the sensors of the sensor unit 109 shown in FIG. 4, specifically including a temperature sensor 502, a sound sensor 503, a foot pressure sensor 504, and a barometric pressure sensor 505.

[0119] In use, the temperature sensor 502 is configured to measure the temperature and generate corresponding temperature data. This temperature data is transmitted to the data processor 107a. The data processor 107a is configured to use this temperature data to calibrate the sensor data from the sensor unit 109, taking into account, if necessary, changes (drift) in the output of the sensor unit 109 due to changes in the temperature to which the system is exposed.

[0120] In some examples, data processor 107a is configured to process sensor data generated by sound sensor 503, foot pressure sensor 504, and barometric pressure sensor 505 to generate walking parameter data.

[0121] In use, foot pressure sensor 504 is typically arranged to detect pressure changes caused by a subject's contact with the ground. For example, foot pressure sensor 504 can be provided by a two-dimensional pressure sensing pad configured to be arranged across the entire improved sole base or a part of the base so as to measure the pressure at different contact points of the foot when the subject's foot contacts the ground. Foot pressure sensor 504 is configured to generate pressure data. Walking characterization function 113 is configured to use the pressure data when generating walking parameters. For example, walking characterization function 113 can use the pressure data to determine when the subject's foot is in contact with the ground, and can also use it to determine when a specific area of the subject's foot (e.g., the ball of the big toe and the heel) is in contact with the ground. Further information related to the subject's walking analysis can be determined from pressure data such as the impact force when the subject contacts the ground with the foot or a specific part of the foot.

[0122] In use, sound sensor 503 is configured to detect sounds in the area of the subject's foot and generate corresponding sound data. In some embodiments, the walking characterization function is configured to use the sound data to classify the type of surface on which the subject is moving (walking, running), and the classification result can be used to improve the algorithm used to estimate the subject's walking parameters. In some examples, the sound data can be used to detect the type or location of the subject's activity.

[0123] In use, the barometric pressure sensor 505 is configured to detect the barometric pressure around the shoe and generate corresponding barometric pressure sensor data. This barometric pressure sensor data may be used by the altitude detection function of the data processor 107a configured to receive sensor data from the barometric pressure sensor and generate corresponding altitude data. This altitude data can be used, for example, as part of an exercise program, to track the vertical movement of the subject while wearing the shoes.

[0124] In some embodiments, the altitude detection function can be incorporated into the travel distance analysis function, as will be described in more detail below.

[0125] Those skilled in the art will understand that the arrangement of the components of the system is an example of how to arrange the system according to the embodiments of the present disclosure, and that the components of the system can be specified in any suitable alternative manner.

[0126] For example, in other configurations, the intervention system may have a personal computer ("PC"), a tablet computer, a smartphone, or a similar personal computing device, and may include program parameters stored in a memory suitable for such a device.

[0127] In some embodiments, each sensor module and the remote intervention system can communicate directly via an appropriate data link, i.e., without an intermediate data network and / or intermediate base station as shown in Figure 1a. For example, the remote intervention system and each sensor module can communicate data with each other via Bluetooth, WiFi, or a similar short-range wireless protocol.

[0128] In embodiments of the present disclosure, the sensor module can be configured to stimulate any suitable area on the back (plantar surface) of the subject's foot (by positioning the vibration actuator relative to the sole of the footwear).

[0129] These regions include the first metatarsophalangeal joint, the fifth metatarsophalangeal joint, the heel region, the thumb region, and the medial longitudinal arch. Examples of these regions are shown in FIG. 6. In an example of footwear incorporating a single vibration actuator, the actuator can be placed at any position, but one of ordinary skill in the art will recognize that other positions not shown in FIG. 6 are also possible.

[0130] In some examples, multiple vibration actuators may be provided in each piece of footwear. In such examples, the sensor module can be configured such that the vibration actuators are arranged to provide a sensory stimulus to any suitable combination of regions on the underside of the subject's foot. For example, a first vibration actuator can be arranged to stimulate the position of the foot in the region of the first metatarsophalangeal joint, a second vibration actuator can be arranged to stimulate the position of the foot in the region of the fifth metatarsophalangeal joint, and a third vibration actuator can be arranged to stimulate the position of the foot in the heel region. In certain other embodiments, a fourth vibration actuator can be arranged to stimulate the position of the foot in the thumb region.

[0131] In some embodiments, the number and position of the vibration actuators are selected based on the type of treatment or training being administered to the subject. This is because, for example, stimulation at different locations can elicit different responses in different patient groups.

[0132] In the above examples, since the vibration of the foot stimulation is "sensory", the subject can consciously recognize the vibration. This is an example of a "tactile cue", and the subject receives the "cue" through a tactile stimulus that can be consciously detected.

[0133] However, in some cases, such as when vibration is applied as a treatment for patients with diabetic neuropathy or when vibration is applied to prevent falls or deal with foot freezing, even when the subject cannot consciously perceive the vibration, subliminal vibration can be applied such that the vibration causes nerve stimulation and produces desired effects such as improving balance and walking. In such cases, the vibration actuator or the foot stimulation vibration generated by the vibration actuator is subliminal vibration that the subject cannot consciously perceive.

[0134] In particular, in cases where subliminal vibration is generated, the data processor associated with each footwear can be configured to calibrate the vibration generated by the vibration actuator (or each vibration actuator), taking into account that different subjects have different perception threshold levels, and these perception thresholds vary depending on different regions of the subject's foot.

[0135] To facilitate this, the data processor associated with each footwear can be configured to control the vibration actuator (or each vibration actuator) to repeatedly step through a sequence of different vibration levels until a vibration level is specified, i.e., until the vibration level is just below the subject's sensory perception for the region of the subject's foot that the vibration actuator stimulates. This calibration process can be performed in conjunction with an external device such as a mobile computing device, such as a smartphone, connected to the data processor via a data transceiver and an appropriate wireless link.

[0136] The different vibration levels can be provided by a vibration actuator that vibrates at different frequencies (e.g., when the vibration actuator is provided by an electric motor having a weight eccentrically mounted on the shaft of the motor) and / or a vibration actuator that vibrates at different amplitudes (e.g., when the vibration actuator is provided by a linear electromagnetic actuator (a "tactile") such as a voice coil).

[0137] In this way, when the calibration process is completed, the vibration level (usually composed of vibration frequency and / or vibration amplitude) is determined for each vibration actuator and is used during the operation of the system.

[0138] In some examples, the data processor of each footwear controls the vibration actuator (or each vibration actuator) and uses "probabilistic resonance" to generate vibrations for sole stimulation. In such examples, the vibrations for sole stimulation are generated according to a random pattern (usually effective for nerve stimulation). For example, the vibration actuator can be configured to apply the vibrations for sole stimulation in an "on / off" pattern, and the time between "on" and "off" randomly varies, for example, between 0.01 seconds and 0.09 seconds.

[0139] In some examples, the sensory stimulation device according to the embodiments of the present disclosure can be incorporated into a modified insole that is insertable and removable from the footwear. An example of such an embodiment is shown in FIG. 7. FIG. 7 is a simplified schematic diagram showing a footwear 701 having a sole 702 and an upper 703 (the sole 702 and the upper 703 are shown in dashed lines and are transparently displayed), and otherwise conventional. A removable modified insole 704 is incorporated, and an assembly 705 having a vibration generating device is shown inside.

[0140] As can be understood, the removable modified insole 704 can be removed from the footwear 701 and inserted into another footwear. This enables, for example, the use of the modified insole 704 with the footwear of multiple subjects or with multiple footwear of the same subject. The modified insole 704 may have a washable and / or disinfectable outer surface, which enables the modified insole 704 to be washed, for example, for hygienic purposes, after being used with the footwear of a first subject and before being used with the footwear of a second subject.

[0141] In the example described with reference to FIG. 1a, all the components related to detecting the movement of the subject and applying the sensory stimulus are incorporated into a single sensory stimulus unit. However, in other examples, these components may be integrated in a different way than footwear. For example, a vibration actuator or a vibration actuator can be attached to a modified sole or a modified insole, while other components, such as sensors and data processors, can be incorporated into other parts of the footwear, such as the upper or the vamp of the shoe.

[0142] Embodiments of the present disclosure can be used in any suitable form of footwear. Such footwear includes shoes such as trainers (sneakers), boots, sandals, etc. In some embodiments, the vibration generating device can be incorporated into specific medical footwear such as CAM (controlled ankle motion) walking boots (moon boots).

[0143] In some embodiments, the sensor module of one or both shoes is configured to perform a moving distance tracking function. The moving distance tracking function is configured to track the distance the shoe has moved and generate corresponding moving distance data.

[0144] The moving distance analysis function can be set to analyze the moving distance data to determine moving patterns related to the movement of the shoe (e.g., total moving distance, average moving time, maximum / minimum moving distance over a certain period, etc.) and generate corresponding moving distance analysis data. And the moving distance analysis data can be used to optimize programs such as treatments, motion assistance, games, training, etc. provided by the system. For example, an expert (such as a doctor) can manually change the program parameters stored in the program parameter database based on the moving distance pattern of the subject.

[0145] The moving distance tracking function can be implemented by any suitable means. For example, the moving distance tracking function can be realized by a data processor on the sensor module of one or both shoes, and the sensor module can further include a position tracking device (e.g., a Global Navigation Satellite System (GNSS) receiver, such as a GPS receiver). The data processor is configured to receive position data from the position tracking device and generate moving distance data therefrom. In other examples, the movement tracking function can be configured to use sensor data collected by a sensor unit (e.g., estimating the number of steps of the subject and estimating the total distance traveled), and generate moving distance data based thereon.

[0146] FIG. 8 provides a schematic diagram of a sensor module arranged for this purpose. FIG. 8 shows a sensor module corresponding to the sensor module referred to in FIG. 3, and further includes a position tracking device 801 provided by a GNSS receiver such as a GPS receiver.

[0147] As described above, in some embodiments, by incorporating an altitude detection function into the moving distance analysis function, altitude-related movement patterns (e.g., the number of meters ascended and / or descended over a given period) can also be considered when generating moving distance analysis data.

[0148] In some embodiments, the system comprises a further function that enables it to generate a sensory stimulus for a further purpose.

[0149] For example, in some embodiments, the system is configured to provide a tactile cue for prompting the subject during training or testing.

[0150] Such cues also include cueing the subject to perform actions such as starting, stopping, turning, sitting, standing, etc.

[0151] Such embodiments can be implemented in any suitable manner.

[0152] The data processor of the sensor unit is equipped with a tactile cue generation function.

[0153] For example, during training or treatment sessions, by sequentially generating tactile cue vibrations, the subject can be made to start walking, stop walking, and start walking again, and so on.

[0154] In the above exemplary embodiment, the vibration actuator of the sensor module is positioned and configured such that the sensory stimulus is mainly applied to the underside (lower side) of the subject's foot, i.e., the sole of the foot.

[0155] However, in other embodiments, the sensor module may be alternatively or additionally configured to provide a sensory stimulus to other areas of the subject's foot. For example, in some embodiments, a footwear incorporating a sensor module substantially corresponding to the above, except that the vibration actuator of the sensor module or the vibration actuator of the sensor module is positioned and configured to provide a sensory stimulus to the subject's ankle or the area closest to the subject's ankle.

[0156] Figure 9a provides a simplified schematic diagram of such an embodiment. Figure 9a shows a footwear 901a including a sensor module 902 of the above type and including, for example, all the components depicted in Figure 3. As can be seen from Figure 9a, the sensor module 902 is attached to an item of the footwear 901a at a position such that the sensory stimulus is applied to the distal part of the subject's ankle during use.

[0157] In a further embodiment, a footwear incorporating a sensor module substantially corresponding to the above-described sensor module is provided. However, the vibration actuator of the sensor module or the vibration actuator is positioned and configured to provide a sensory stimulus to the upper (upper) side of the subject's foot.

[0158] FIG. 9b provides a simplified schematic view of such an embodiment. FIG. 9b shows an item of footwear 901b that includes a sensor module 903 of the type described above and, for example, all of the components depicted in FIG. 3. As can be seen from FIG. 9b, the sensor module 902 is worn on the footwear 901a in a position such that a sensory stimulus is applied to the upper (superior) side of the subject's foot during use.

[0159] All of the functions (including the appended claims, abstract, and drawings) disclosed herein, and / or all of the steps of the disclosed methods or processes, can be combined in any combination, except combinations where at least some of the functions and / or steps are mutually exclusive. Each function (including the appended claims, abstract, and drawings) disclosed herein can be replaced by an alternative function that serves the same, equivalent, or similar purpose, unless expressly stated otherwise. Accordingly, unless expressly stated otherwise, each feature disclosed is merely an example of a general series of equivalent or similar features. The present invention extends to novel examples, or novel combinations, of the features (including the appended claims, abstract, and drawings) disclosed herein, or novel examples, or novel combinations, of the steps of the disclosed methods or processes.

[0160] Regarding the use of plural and / or singular terms in this disclosure, those skilled in the art can convert from plural to singular and / or from singular to plural, depending on the context and / or application. For clarity, various singular / plural combinations can be explicitly defined in this disclosure.

[0161] One of ordinary skill in the art will generally understand that the terms used herein, particularly those used in the appended claims, are generally intended to be “open” terms (e.g., the term “comprising” should be interpreted to mean “including but not limited to,” the term “having” should be interpreted to mean “having at least,” the term “including” should be interpreted to mean “including but not limited to,” etc.). One of ordinary skill in the art will understand that if a specific numerical value is intended in the language of the introduced claim, that intent will be expressly recited in the claim, and if there is no such recitation, there is no such intent. To assist understanding, for example, the following appended claims may use introductory phrases such as “at least one” and “one or more” to introduce the language of the claim. However, the use of such expressions should not be construed as implying that the introduction of a claim element by the indefinite article “a” or “an” limits a particular claim that includes the introduced claim element to embodiments in which there is only one such element. This is the same even if the same claim includes introductory phrases such as “one or more” or “at least one” or indefinite articles such as “a” or “an” (e.g., “a” and / or “an” should be interpreted to mean “at least one” or “one or more”). This also applies to the definite article used to introduce a claim recitation. Further, even if a specific number of the introduced claim is expressly recited, one of ordinary skill in the art will understand that such recitation should be interpreted to mean at least the recited number (e.g., a mere recitation of “twice” means at least twice, or two or more times, if there are no other modifying phrases).

[0162] It will be understood that various embodiments of the present disclosure are described herein for purposes of illustration and that various modifications can be made without departing from the scope of the present disclosure. Accordingly, the various embodiments disclosed herein are not limiting, and the true scope is shown by the following claims.

Claims

1. A system that provides interventions based on detected gait kinesiology for therapy, training, games, or mobility assistance, At least one footwear incorporating one or more sensors, a data processor, and a wireless communication unit, The system includes a remote intervention system configured to provide an intervention to elicit a response from a subject wearing the aforementioned footwear, The one or more sensors are configured to generate sensor data related to the subject's movements. The data processor is configured to process the sensor data and generate gait parameter data related to the gait kinematics of the subject. The wireless communication unit is configured to communicate the walking parameter data to the remote intervention system. system.

2. The system according to claim 1, wherein the remote intervention system is configured to provide sensory intervention.

3. The system according to claim 1, wherein the remote intervention system comprises at least one stimulator, such as a spinal stimulator, a deep brain stimulator, or a muscle stimulator.

4. The system according to claim 1, wherein the remote intervention system includes a simulator such as a virtual reality system or an augmented reality system.

5. The system according to claim 1, wherein the at least one footwear further comprises a memory, the memory configured to store the sensor data and / or walking parameter data.

6. The system according to claim 5, wherein the data processor is configured to compare the sensor data and / or walking parameter data with stored sensor data and / or walking parameter data in order to determine whether the sensor data and / or walking parameter data corresponds to a walking event.

7. The system according to claim 6, wherein the data processor is configured to control the wireless communication unit to communicate the walking parameter data to the remote intervention system when it is determined that the sensor data and / or walking parameter data correspond to a walking event.

8. The system according to claim 6, wherein the walking event is at least one of the following: an imminent fall or a state of high risk of falling for the subject; an imminent cessation of walking or a state of high risk of freezing of gait; a deviation from a movement desirable for the subject; or maintenance of a movement form desirable for the subject.

9. The system according to claim 5, wherein the data processor is configured to periodically generate walking parameter data at predetermined intervals and to store the generated walking parameter data in memory.

10. The system according to claim 1, wherein the gait parameter data includes data relating to walking speed, step / stride speed, step / stride length, swing time variability, stride length, stride duration, step / stride width, rhythm, variability, asymmetry, posture control, gait characteristics, pace, walking speed, swing phase ratio, heel-off, toe-off, heel-strike, sole-strike, gait variability, and gait stability.

11. The system according to claim 1, wherein one or more sensors, a data processor, a memory, and a wireless communication unit are embedded in the sole or insole of the footwear.

12. The system according to claim 1, wherein the sensor has one or more inertial measuring units having one or more accelerometers, gyroscopes, and magnetometers.

13. The system according to claim 12, wherein the sensor further includes one or more of the following: a foot pressure sensor for detecting pressure changes caused by the subject's contact with the ground; a temperature sensor for detecting ambient temperature; a pressure sensor for detecting atmospheric pressure; and a sound sensor.

14. The at least one footwear further incorporates a distance tracking function configured to generate distance data related to the distance the footwear has traveled, The system according to claim 1, wherein the data processor is configured to process the travel distance data and generate travel distance analysis data.

15. The system according to claim 14, wherein the wireless communication unit is configured to communicate the travel distance analysis data to the remote intervention system.

16. The system according to claim 1, wherein at least one footwear comprises a rechargeable battery for supplying power to incorporated components.

17. A method for providing a detected gait kinesiology-based intervention for therapy, training, games, or mobility assistance, A step of generating sensor data related to the movements of the person wearing the footwear, The footwear is used to process the sensor data and generate walking parameter data related to the subject's walking motion, and the steps are as follows: The steps include: communicating gait parameter data from the footwear to a remote intervention system in order to provide an intervention; A method for controlling the remote intervention system to provide an intervention that elicits a response from a person wearing the footwear.

18. A configuration suitable for footwear, the configuration including one or more sensors, a data processor, and a wireless communication unit, The one or more sensors are configured to generate sensor data related to the movement of a person wearing footwear. The data processor is configured to process the sensor data and generate gait parameter data related to the gait kinematics of the subject. The wireless communication unit is configured to communicate the walking parameter data to a remote intervention system.

19. Footwear to which the configuration described in claim 18 is applied.

20. A pair of footwear comprising a footwear according to claim 19 for the left foot and a footwear according to claim 19 for the right foot.

21. A computer program for use in the system described in claim 1, which runs on a data processor incorporated in footwear, and which, when run on the data processor, controls the data processor to perform a method, the method is A step of generating sensor data related to the movements of a person wearing footwear, The steps include: processing the sensor data using footwear to generate gait parameter data related to the gait kinematics of the subject; The steps include: communicating the gait parameter data from the footwear to a remote intervention system in order to provide an intervention to elicit a response from a person wearing the footwear; Having, Computer program.

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