A system and method for improving the estimation of walking speed and distance by fusing activity monitoring devices located in the same location.

Abstract

This disclosure is directed toward systems and methods adapted to improve gait tracking of individuals with atypical or abnormal gait patterns by fusing activity monitoring devices located in the same location. As described herein, hospital staff and patients may be equipped with activity monitoring devices, which are used by the systems and methods to detect the proximity of such devices and then update parameters used to track the patient's gait. For example, if two or more devices are detected in close proximity (e.g., a nurse is walking with a patient), estimates from both devices are compared. Both estimates are then updated by adjusting model parameters, for example, by giving both estimates equal weight to reach an average speed, or by performing weighted adjustments based on reliability parameters indicating the reliability of the individual estimates.

Description

Technical Field

[0001] The present disclosure generally relates to systems and methods for monitoring foreign patients, and more specifically, to systems and methods for improving the monitoring of walking metrics of patients with an atypical gait by the fusion of activity monitoring devices located in the same place.

Background Art

[0002] Walking metrics such as walking speed and walking distance are important for estimating a patient's condition and / or changes in the patient's condition. For example, there are algorithms for estimating walking speed from accelerometer data from wearable devices.

Summary of the Invention

Problems to be Solved by the Invention

[0003] Such algorithms can function well for certain types of individuals, but are biased or less accurate for others, especially patients with an atypical or abnormal gait pattern (such as by using walking aids). Further, such walking estimations can be improved in some situations (e.g., when outdoors) by using GPS data to calibrate or personalize the monitoring algorithm, but in an indoor hospital or clinical environment, this approach becomes less reliable / accurate.

Means for Solving the Problems

[0004] This disclosure is directed toward systems and methods adapted to improve gait tracking of individuals with atypical or abnormal gait patterns by fusing activity monitoring devices located in the same location. As described herein, hospital staff and patients may be equipped with activity monitoring devices, which are used to detect the proximity of such devices and then update parameters used by the system and method to track the patient's gait. For example, if two or more devices are detected in close proximity (e.g., a nurse is walking with a patient), estimates from both devices are compared. Both estimates can then be updated by adjusting model parameters, for example, by giving both estimates equal weight to reach an average speed, or by performing weighting adjustments based on reliability parameters indicating the reliability of the individual estimates.

[0005] Embodiments of the present disclosure provide a patient monitoring system configured to measure one or more gait indicators related to a subject. The system may include a computer-readable storage medium storing machine-readable instructions executed by one or more processors, and one or more processors configured to perform, by means of the machine-readable instructions stored in the computer-readable storage medium, (i) detecting when a subject device and an assistant device are within a predetermined proximity to each other, (ii) determining whether the subject device and the assistant device remain within the predetermined proximity for at least one of a predetermined time and / or a predetermined distance, (iii) obtaining subject data of a first gait indicator related to the subject from the subject device, (iv) obtaining assistant data of a first gait indicator related to the assistant from the assistant device, and (v) estimating the subject's true gait indicator based on the subject data obtained via the subject device and the assistant data obtained via the assistant device.

[0006] In one embodiment, the patient monitoring system may further include a subject device configured to be worn by a subject, the subject device having at least a first sensor configured to measure the subject's gait index.

[0007] In one embodiment, the subject device may have the computer-readable storage medium and the one or more processors.

[0008] In one embodiment, the patient monitoring system may further include an assistant device configured to be worn by an assistant, the assistant device having at least a second sensor configured to measure the assistant's gait index.

[0009] In one embodiment, the assistant device may have the computer-readable storage medium and the one or more processors.

[0010] According to another embodiment of the present disclosure, a non-temporary computer-readable storage medium storing machine-readable instructions is provided. When executed by one or more processors, the machine-readable instructions cause the one or more processors to perform operations including detecting when a subject device and an assistant device are in a predetermined proximity to each other, determining whether the subject device and the assistant device remain in a predetermined proximity for at least one of a predetermined time and / or a predetermined distance, obtaining subject data of a first gait index related to the subject from the subject device, obtaining assistant data of a first gait index related to the assistant from the assistant device, and estimating the true gait index of the subject based on the subject data obtained via the subject device and the assistant data obtained via the assistant device.

[0011] A further embodiment of the present disclosure provides a computer implementation method for measuring one or more gait indicators related to a subject. The method may include steps of: detecting when a subject device and an assistant device are within a predetermined proximity to each other; determining whether the subject device and the assistant device remain within the predetermined proximity for at least one of a predetermined time and / or a predetermined distance; obtaining subject data of a first gait indicator related to the subject from the subject device; obtaining assistant data of a first gait indicator related to the assistant from the assistant device; and estimating the subject's true gait indicators based on the subject data obtained via the subject device and the assistant data obtained via the assistant device.

[0012] These and other aspects of various embodiments are evident and will be described below from the embodiments. [Brief explanation of the drawing]

[0013] In drawings, the same reference numeral generally refers to the same part across different drawings. Furthermore, drawings are not necessarily to a fixed scale; instead, they generally focus on illustrating the principles of various embodiments. [Figure 1] Figure 1 shows the use of a patient monitoring system according to a particular aspect of this disclosure. [Figure 2A] Figure 2A shows the fusion of activity monitoring devices located in the same location according to an aspect of this disclosure. [Figure 2B] Figure 2B is another diagram showing the fusion of activity monitoring devices located in the same location according to a further aspect of this disclosure. [Figure 3] Figure 3 is a flowchart showing a method for measuring subject-related gait indices according to a particular aspect of this disclosure. [Modes for carrying out the invention]

[0014] This disclosure is directed toward a system and method adapted to improve gait tracking of individuals with atypical or abnormal gait patterns. As described herein, measuring gait metrics such as gait speed and gait distance is important for estimating a patient's condition and / or changes in the patient's condition. While various algorithms exist for estimating gait speed (e.g., from accelerometer data from wearable devices), such algorithms do not work well for patients with atypical or abnormal gait patterns (e.g., due to the use of walking aids). Furthermore, conventional methods that improve the sensitivity and / or accuracy of gait tracking using GPS data have limited applicability in indoor hospitals and clinical settings. Therefore, the system and method of this disclosure utilizes the fusion of activity monitoring devices located in the same location to improve and / or enhance gait tracking of individuals with atypical or abnormal gait patterns without using GPS tracking.

[0015] Referring to Figure 1, a diagram is shown illustrating the operation of a patient monitoring system 100 configured to measure one or more gait indicators related to a subject 102, according to various aspects of this disclosure. As described herein, subject 102 is a patient who has an atypical or abnormal gait pattern, for example, due to the use of walking aids, injuries affecting the patient's gait, and / or similar. Subject 102 may be equipped with one or more activity monitoring devices, such as activity monitoring device 104. Similarly, one or more other individuals, such as individual 106, may also be equipped with one or more activity monitoring devices, such as activity monitoring device 108.

[0016] In some embodiments, the activity monitoring devices 104, 108 can be configured to be worn by a subject 102 and / or other individuals 106. That is, devices 104, 108 can be wearable devices. In certain embodiments, each device 104, 108 may have at least one sensor 112, 114 configured to measure gait metrics of the corresponding individuals 102, 106. For example, each device 104, 108 may have one or more accelerometers, barometers, photoplethysmography sensors, and / or similar. In certain embodiments, gait metrics measured by devices 104, 108 may include, but are not limited to, walking speed and / or walking distance.

[0017] The patient monitoring system 100 can be configured to detect when one or more activity monitoring devices 108 enter a predetermined proximity P of an activity monitoring device 104 worn by a subject 102. As described herein, hospital staff 106 and patient 102 may be equipped with activity monitoring devices 104, 108, which are then used by the system 100 to detect the proximity of such devices 104, 108 and to update parameters used to track the patient 102's gait. For example, in a particular embodiment, individual 106 is hospital staff, such as a physiotherapist, assisting patient 102 in receiving physiotherapy, and it is valuable to measure specific gait indicators of patient 102 during physiotherapy.

[0018] As described herein, an individual 106 assisting patient 102 may be referred to as assistant 106, and an activity monitoring device 108 worn by this assistant 106 may be referred to as assistant device 108. Since various hospital staff and / or other medical professionals may be in a position to assist many different patients 102, each of these individuals 106 may be equipped with an assistant device 108.

[0019] In some embodiments, proximity P may be predetermined based on the type of activity being monitored, or it may be set collectively for all devices 104, 106. Proximity P may be predetermined to indicate an assistant 106 (such as hospital staff) assisting a patient 102. In some embodiments, proximity P may be predetermined to be about 2 meters, including less than about 2 meters.

[0020] In one embodiment, when two or more devices 104, 108 are detected in close proximity P, the system 100 can acquire gait estimation data from both devices 104, 108 and compare such data to improve the accuracy and / or reliability of tracking related to the subject 102.

[0021] In some embodiments, the system 100 may be configured to determine whether the subject device 104 and the assistant device 108 have remained within a predetermined proximity P for at least a predetermined time and / or distance before using data from both devices 104, 108, as described herein. For example, if the assistant device 108 remains within proximity P of the subject device 102 for only a short period of time, this indicates that the assistant 106 has only passed by the subject 102 and should not be used for tracking gait indicators.

[0022] In some embodiments, system 100 may obtain subject data of one or more walking metrics related to subject 102 from subject device 104, and may obtain assistant data of one or more walking metrics related to assistant 106 from assistant device 108. In an embodiment, system 100 may obtain subject data and assistant data of at least one common walking metric related to subject 102 and assistant 106, respectively. For example, in some embodiments, system 100 may obtain subject data of a first walking metric related to subject 102 from subject device 104, and may obtain assistant data of the first walking metric related to assistant 106 from assistant device 108.

[0023] In an embodiment, when the subject data and the assistant data are obtained, true walking metrics (e.g., walking speed, walking distance) can be estimated based on those data. For example, in a particular embodiment, the algorithm and / or parameters used by subject device 104 to determine the walking metric may be updated based on the assistant data obtained from assistant device 108.

[0024] In some embodiments, optionally, a reliability score for each output can determine a weighting factor for an individual estimate. For example, as shown in FIG. 2A, the walking speeds of a healthcare provider (HCP) and a patient (Patient 1) are estimated separately using assistant device 108 and subject device 104, respectively. However, neither estimate is completely accurate, but by averaging these estimates, a value close to the actual speed of patient 102 can be determined. In some embodiments, a weighted result may be obtained by assigning a higher reliability value to the assistant data (i.e., data related to the healthcare provider (HCP)).

[0025] For example, if two or more devices are detected in close proximity (e.g., a nurse walking with a patient), estimates from both devices are compared. Both estimates are then updated by adjusting model parameters, for example, by giving both estimates equal weight to reach the average speed, or by performing weighted adjustments based on reliability parameters that indicate the reliability of the individual estimates.

[0026] It should be understood that the weights of the adjustments are adjusted based on reliability parameters, for example, so that the reliability score depends on the role of the individuals 102, 106 wearing the devices 104, 108. Furthermore, it should be understood that the reliability score may improve over time, for example, after multiple calibrations. In embodiments, different reliability scores may exist for different walking speeds (for example, the algorithm may become accurate for a nurse's slow walking but not for faster walking). In further embodiments, when individuals 102, 106 wear the devices 104, 108 outside the hospital and additional tracking information (e.g., GPS information) is available, such information may be used to adjust other algorithms used to estimate the walking index according to this disclosure.

[0027] In some embodiments, the algorithms used by devices 104 and 108 to determine gait indices may be the same or may differ for each individual 102 and 106. That is, each device 104 and 108 and each individual 102 and 106 may run a different algorithm. In some embodiments, a switch may be made to a different algorithm that gives results closer to the actual speed based on acquired subject data and assistant data.

[0028] In the embodiment, instead of moving entirely toward the same actual speed, a maximum update threshold may be set to prevent overcorrection (i.e., the true gait index cannot exceed a certain percentage difference from the observed value).

[0029] As described herein, System 100 includes a computer-readable storage medium storing machine-readable instructions to be executed by one or more processors, and one or more processors configured to perform one or more of the operations described above by the machine-readable instructions stored in the computer-readable storage medium. In a particular embodiment, a subject device 104 performs one or more of the operations described above, i.e., the subject device 104 has the computer-readable storage medium and the one or more processors. In a further embodiment, an assistant device 108 performs one or more of the operations described above, i.e., the assistant device 108 has the computer-readable storage medium and the one or more processors. In yet another embodiment, an external device 110 (e.g., a patient monitor) is configured to perform one or more of the operations described above, i.e., the external device 110 has the computer-readable storage medium and the one or more processors.

[0030] Referring to Figure 3, a computer implementation method 300 is provided for measuring one or more gait indicators related to a subject 102. As shown, the method 300 includes the steps of: detecting in step 310 when a subject device and an assistant device are within a predetermined proximity to each other; determining in step 320 whether the subject device and the assistant device remain within a predetermined proximity for at least one of a predetermined time and / or a predetermined distance; obtaining subject data of a first gait indicator related to the subject from the subject device in step 330; obtaining assistant data of a first gait indicator related to the assistant from the assistant device in step 340; and estimating the true gait indicator of the subject based on the subject data obtained via the subject device and the assistant data obtained via the assistant device.

[0031] All combinations of the concepts described above, and any additional concepts discussed in more detail below, should be understood as being part of the subject matter of the invention disclosed herein (provided that such concepts are not mutually contradictory). In particular, all combinations of the claimed subject matter at the end of this disclosure should be understood as being part of the subject matter of the invention disclosed herein. Any technical terms used expressly herein, appearing in any disclosure incorporated by reference, should be understood as having the meaning most in agreement with the specific concepts disclosed herein.

[0032] All definitions defined and used herein should be understood to supersede dictionary definitions, definitions in documents incorporated by reference, and / or the ordinary meanings of the terms defined.

[0033] The indefinite articles “a” and “an” used in the specification and claims should be understood to mean “at least one” unless the opposite is explicitly stated.

[0034] The term “and / or” as used in the specification and claims should be understood to mean “either one or both” of the linked elements, that is, elements that exist jointly in some cases and disjunctly in others. Similarly, any multiple elements listed using “and / or” should be interpreted as “one or more” of the linked elements. Other elements other than those specifically identified by the “and / or” clauses may exist, whether or not they relate to those specifically identified elements.

[0035] As used in the specification and claims, “or” should be understood to have the same meaning as “and / or” as defined above. For example, when dividing items in a list, “or” or “and / or” should be interpreted as being compatible, that is, including at least one of the elements of the list, but possibly two or more, and optionally including additional items not on the list. Only terms with particular clear indication, such as “only one of” or “exactly one of” or “consisting of” as used in the claims, refer to including exactly one of the elements of the list. In general, the term “or” as used herein should be interpreted simply as indicating an exclusive choice (i.e., one or the other, but not both) when accompanied by an exclusive word such as “either,” “one of,” “only one of” or “exactly one of.”

[0036] As used in the specification and claims, the term “at least one” in relation to a list of one or more elements should be understood to mean at least one element selected from any one or more of the elements of the list, but not necessarily having to include at least one of every element specifically enumerated in the list of elements, and not excluding any combination of elements in the list of elements. This definition also allows for the optional presence of elements other than those specifically identified in the list of elements, which are referred to by the term “at least one,” regardless of whether they are related to the specifically identified elements.

[0037] The terms "first," "second," "third," etc., are used herein to describe various elements or components, but it will be understood that these elements or components should not be limited by these terms. These terms are used solely to distinguish one element or component from another. Accordingly, the first element or component described below may be referred to as the second element or component without departing from the teaching of the concept of the present invention.

[0038] Unless otherwise specified, when we say that an element or component is “connected,” “joined,” or “adjacent” to another element or component, it should be understood that the element or component is directly connected to or joined to the other element or component, or that there is an intervening element or component. That is, these and similar terms include cases where one or more intermediate elements or components are used to connect two elements or components. However, when we say that an element or component is “directly connected” to another element or component, this includes only cases where the two elements or components are connected to each other without any intermediate or intervening elements or components.

[0039] In the claims and specification, all transitional phrases such as “having,” “including,” “carrying,” “possessing,” “encompassing,” “including,” “holding,” and “composed of” should be understood as open-ended, meaning they include but are not limited to them. Only the transitional phrases “consisting of” and “essentially consisting of” are closed or semi-closed transitional phrases, respectively.

[0040] Unless otherwise explicitly stated, it should be understood that in any method claimed herein that includes two or more steps or actions, the order of the steps or actions of the method is not necessarily limited to the order in which the steps or actions of the method are enumerated.

[0041] The above-mentioned examples of the subject matter described can be implemented in any of many ways. For example, some embodiments are implemented using hardware, software, or a combination thereof. When any embodiment is implemented at least partially in software, the software code can be executed on any suitable processor or set of processors, whether it is provided on a single device or computer, or distributed across multiple devices / computers.

[0042] This disclosure can be implemented as a system, method, and / or computer program product in any possible level of technical detail. The computer program product may include one or more computer-readable storage media having computer-readable program instructions for causing a processor to perform aspects of this disclosure.

[0043] A computer-readable storage medium can be a tangible device capable of holding and storing instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the devices described above. A less-than-complete list of more specific examples of computer-readable storage media includes portable computer diskettes, hard disks, RAM (random access memory), ROM (read-only memory), EPROM (erasable programmable read-only memory) or flash memory, SRAM (static-RAM), CD-ROMs, DVDs, Memory Sticks®, floppy disks®, mechanically encoded devices such as punch cards or raised structures in grooves on which instructions are recorded, and any suitable combination of the above. The computer-readable storage media used herein should not be interpreted as being transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through optical fiber cables), or electrical signals transmitted through wires.

[0044] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to each computer / processing device, or downloaded via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network, to an external computer or external storage device. The network may include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computer / processing device receives the computer-readable program instructions from the network and transfers them to a computer-readable storage medium in each computer / processing device for storage.

[0045] Computer-readable program instructions for performing the operations of the Disclosure may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or source code or object code written in any combination of one or more programming languages, such as object-oriented programming languages ​​like Smalltalk or C++, and procedural programming languages ​​like the “C” programming language or similar programming languages. Computer-readable program instructions may run entirely on the user's computer, partially on the user's computer, run as a standalone software package, partially on the user's computer and partially on a remote computer, or run entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or wide area network (WAN), or may be connected to an external computer (for example, via the Internet using an Internet service provider). In some examples, for instance, an electronic circuit having a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA) can execute computer-readable program instructions by utilizing state information of computer-readable program instructions and personalizing the electronic circuit in order to perform an aspect of the present disclosure.

[0046] Aspects of the present disclosure are described herein with reference to flowcharts and / or block diagrams of the methods, apparatus (systems), and computer program products illustrated herein. It should be understood that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0047] Computer-readable program instructions are supplied to the processor of a dedicated computer or other programmable data processing device to generate a machine that creates means for performing functions / operations defined in the blocks of a flowchart and / or block diagram, through which instructions are executed via the processor of the computer or other programmable processing device. These computer-readable program instructions may also be stored in a computer-readable storage medium that can instruct a computer, a programmable data processing device, and / or other device to function in a particular way, such as having a product that has instructions that perform a manner of function / operation defined in the flowchart and / or block diagram, or in the blocks.

[0048] Computer-readable program instructions can also be loaded into a computer, other programmable device, or other device, and a series of action steps performed on a computer, other programmable data processing device, or other device can generate a computer-executed process, such that instructions executed on the computer, other programmable data processing device, or other device perform functions / operations defined in a flowchart and / or block diagram, or blocks.

[0049] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible embodiments of the systems, methods, and computer program products, as illustrated by various examples of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or part of an instruction having one or more executable instructions for performing a defined logical function. In some alternative implementations, the functions represented in a block may occur outside the order shown in the figure. For example, two consecutively shown blocks may actually be executed substantially simultaneously, or blocks may be executed in reverse order depending on the functions they contain. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, are implemented by a dedicated hardware-based system that performs a defined function or operation, or executes a combination of dedicated hardware and computer instructions.

[0050] Other uses are within the scope of the following claims and other claims to which the applicant may be granted rights.

[0051] While several inventive embodiments have been described and illustrated herein, those skilled in the art will readily conceive of various means and / or structures to perform and / or obtain the functions and / or one or more advantages described herein, and each such variation and / or modification will be considered to fall within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily understand that all parameters, dimensions, materials and configurations described herein are illustrative, and that actual parameters, dimensions, materials and / or configurations will depend on the specific application using the teachings of the present invention. Those skilled in the art will recognize many equivalents to the specific inventive embodiments described herein, or can verify them using only routine experimentation. Accordingly, it should be understood that the embodiments described above are presented merely as examples, and that different inventive embodiments than those specifically described and claimed may be implemented within the appended claims and their equivalents. The inventive embodiments of this disclosure cover the individual features, systems, articles, materials, kits and / or methods described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and / or methods is also included within the inventive scope of this disclosure, provided that such features, systems, articles, materials, kits, and / or methods are not contradictory to each other.

Claims

1. In a patient monitoring system configured to measure one or more gait indicators related to a subject, the system comprises: A computer-readable storage medium for storing machine-readable instructions executed by one or more processors, According to the machine-readable instructions stored in the computer-readable storage medium, (i) Detect when the subject device and the assistant device are within a predetermined proximity of each other. (ii) Determining whether the subject device and the assistant device remain within the predetermined proximity for at least one of a predetermined time and / or a predetermined distance, (iii) Obtain subject data of a first gait index related to the subject from the subject device, (iv) Obtaining assistant data of a first gait index related to the assistant from the assistant device, and (v) Estimating the true gait index of the subject based on the subject data acquired via the assistant device and the assistant data acquired via the subject device. One or more processors configured to perform the following: A patient monitoring system having [a specific feature / feature].

2. The patient monitoring system according to claim 1, further comprising a subject device configured to be worn by the subject, the subject device having at least a first sensor configured to measure the subject's gait index.

3. The patient monitoring system according to claim 1 or 2, wherein the subject device further comprises the computer-readable storage medium and the one or more processors.

4. The patient monitoring system according to claim 1, further comprising an assistant device configured to be worn by the assistant, wherein the assistant device has at least a second sensor configured to measure the assistant's gait indicators.

5. The patient monitoring system according to claim 1 or 4, wherein the assistant device further comprises the computer-readable storage medium and the one or more processors.

6. A non-temporary computer-readable storage medium storing machine-readable instructions, wherein when the machine-readable instructions are executed by one or more processors, the one or more processors... To detect when the subject device and the assistant device are within a predetermined proximity of each other. To determine whether the subject device and the assistant device remain within the predetermined proximity for at least one of a predetermined time and / or a predetermined distance, To obtain subject data of a first gait index related to the subject from the subject device, To acquire assistant data of a first gait index related to the assistant from the aforementioned assistant device, and To estimate the true gait index of the subject based on the subject data acquired via the subject device and the assistant data acquired via the assistant device. A non-temporary computer-readable storage medium that enables the following actions.

7. A computer implementation method for measuring one or more gait indicators related to a subject, wherein the method is: A step of detecting when the subject device and the assistant device are within a predetermined proximity of each other, A step of determining whether the subject device and the assistant device remain within a predetermined proximity for at least one of a predetermined time and / or a predetermined distance, A step of obtaining subject data of a first gait index related to the subject from the subject device, The steps include obtaining assistant data of a first gait indicator related to the assistant from the aforementioned assistant device, and A step of estimating the true gait index of the subject based on the subject data acquired via the subject device and the assistant data acquired via the assistant device. A computer implementation method having

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