Intervention based on detected gait kinematics

Abstract

A system provides detected gait kinematics-based intervention for therapy, training, gaming or exercise assistance. The system includes at least one article of footwear incorporating one or more sensors, a data processor, and a wireless communication unit, and a remote intervention system configured to provide intervention for stimulating a response of a subject wearing the article of footwear. The one or more sensors are configured to generate sensor data associated with motion of a subject. The data processor is configured to process the sensor data to generate gait parameter data associated with gait kinematics of the subject, and the wireless communication unit is configured to communicate the gait parameter data to a remote intervention system.

Description

Technical Field

[0001] The present invention is directed to providing intervention based on detected gait kinematics for treatment, training, gaming or sports assistance. background

[0002] Techniques for providing interventions, such as vibratory stimulation of a person's feet for therapeutic reasons, are known in the art (see, for example, Galica et al., "Subsensory vibrations to the feet reduce gait variability inelderly fallers").

[0003] Typically, these techniques involve monitoring certain aspects of the subject's gait kinematics to identify movements that require application of vibration stimulation, and then applying the relevant vibrations.

[0004] Typically, these techniques are used in motion analysis laboratories. However, some systems have been proposed that can be used outside of a laboratory setting.

[0005] For example, WO2017 / 023864 proposes a system for alleviating knee osteoarthritis by modifying a subject's gait kinematics using electrical or vibrotactile sensory stimulation applied to the subject's foot. SUMMARY OF THE INVENTION

[0006] According to a first aspect of the present invention, there is provided a system for providing intervention based on detected gait kinematics for treatment, training, gaming or sports assistance, the system comprising: at least one article of footwear incorporating one or more sensors, a data processor and a wireless communication unit; and a remote intervention system configured to provide intervention for stimulating a response from a subject wearing the article of footwear, wherein the one or more sensors are configured to generate sensor data associated with the subject's movement; the data processor is configured to process the sensor data to generate gait parameter data associated with the subject's gait kinematics, and the wireless communication unit is configured to transmit the gait parameter data to the remote intervention system.

[0007] Optionally, the remote intervention system is configured to provide sensory intervention.

[0008] Optionally, the remote intervention system comprises at least one stimulation device, such as a spinal stimulation device or a deep brain stimulation device or a muscle stimulation device.

[0009] Optionally, the remote intervention system comprises a simulator, such as a virtual reality system or an augmented reality system.

[0010] Optionally, the at least one article of footwear further comprises a memory, wherein the memory is configured to store sensor data and / or gait parameter data.

[0011] Optionally, the data processor is configured to compare the sensor data and / or gait parameter data with stored sensor data and / or gait parameter data to determine whether the sensor data and / or gait parameter data corresponds to a gait event.

[0012] Optionally, the data processor is configured to control the wireless communication unit to transmit the gait parameter data to the remote intervention system when it is determined that the sensor data and / or the gait parameter data corresponds to a gait event.

[0013] Optionally, the gait event is at least one of: the subject is about to fall or is at a higher risk of falling, is about to gait freeze or is at a higher risk of gait freezing, deviates from the subject's desired movement, and maintains the subject's desired movement form.

[0014] Optionally, the data processor is configured to periodically generate gait parameter data at predetermined intervals and store the generated gait parameter data in a memory. The predetermined interval may be an interval suitable for the determined gait parameter. For example, gait parameter data may be periodically generated at predetermined intervals less than the human reaction time, and the gait parameter data (e.g., gait stability) may be determined without completing a complete stride / stride. For example, the interval may be less than 0.1 seconds. Gait parameter data (e.g., stride length) required to complete a complete stride / stride may be periodically generated at predetermined intervals (cadence) not less than the duration of the subject's stride / stride, or periodically generated at predetermined intervals not less than the duration of a typical stride / stride for humans to perform a specific motion (human motion cadence), such as periodically generated at predetermined intervals not less than 0.5 seconds and not more than 2 seconds (e.g., 1 second).

[0015] Optionally, the gait parameter data includes data related to one or more of the following: gait speed, stride speed / stride speed, step length / stride length, swing time variability, stride length, stride duration, step width / stride width, rhythm, variability, asymmetry, posture control, step characteristics, cadence, gait rate, swing-stance ratio, heel-off, toe-off, heel-strike, foot-flat-event, gait variability and gait stability.

[0016] Optionally, one or more sensors, data processors, memory, and wireless communication units are embedded in the sole or insole of the article of footwear.

[0017] Optionally, the sensor comprises one or more inertial measurement units including one or more of an accelerometer, a gyroscope and a magnetometer.

[0018] Optionally, the sensor further includes one or more of the following: a foot pressure sensor for detecting pressure changes caused by the subject contacting the ground, a temperature sensor for detecting ambient temperature, an atmospheric pressure sensor for detecting atmospheric pressure, and a sound sensor.

[0019] Optionally, the at least one article of footwear further comprises a movement distance tracking device configured to generate movement distance data associated with a distance moved by the article of footwear, and the data processor is configured to process the movement distance data to generate movement distance analysis data.

[0020] Optionally, the wireless communication unit is configured to transmit the movement distance analysis data to a remote intervention system.

[0021] Optionally, at least one article of footwear includes a rechargeable battery for powering components contained within the at least one article of footwear.

[0022] According to a second aspect of the invention, there is provided a method for providing intervention based on detected gait kinematics for treatment, training, gaming or sports assistance, the method comprising: generating, at an article of footwear, sensor data associated with the movement of a subject wearing the article of footwear; at the article of footwear, processing the sensor data to generate gait parameter data associated with the gait kinematics of the subject; transmitting the gait parameter data from the article of footwear to a remote intervention system for providing intervention, and controlling the remote intervention system to provide intervention for stimulating a response from the subject wearing the article of footwear.

[0023] According to a third aspect of the invention, there is provided an arrangement for fitting to an article of footwear, the arrangement comprising one or more sensors, a data processor and a wireless communication unit, wherein the one or more sensors are configured to generate sensor data associated with the movement of a subject wearing the article of footwear; the data processor is configured to process the sensor data to generate gait parameter data associated with the gait kinematics of the subject, and the wireless communication unit is configured to transmit the gait parameter data to a remote intervention system.

[0024] According to a fourth aspect of the present invention, there is provided an article of footwear having mounted thereon an apparatus according to the third aspect of the present invention.

[0025] According to a fifth aspect of the present invention, there is provided a pair of footwear comprising a left-hand article of footwear according to the fourth aspect of the present invention and a right-hand article of footwear according to the fourth aspect of the present invention.

[0026] According to a sixth aspect of the invention, a computer program is provided for running on a data processor incorporated in an article of footwear and for use in a system according to the first aspect of the invention, the computer program comprising instructions which, when implemented on the data processor, control the data processor to perform a method comprising: generating, at the article of footwear, sensor data associated with the movement of a subject wearing the article of footwear; processing, at the article of footwear, the sensor data to generate gait parameter data associated with the gait kinematics of the subject; and transmitting the gait parameter data from the article of footwear to a remote intervention system for providing intervention that stimulates a response from the subject wearing the article of footwear.

[0027] According to an embodiment of the present invention, a system for providing intervention based on detected gait kinematics for the purpose of therapy, training, gaming or sports assistance is provided, the system having an optimized system architecture.

[0028] According to embodiments of the present invention, data related to a subject can be collected outside of a clinical setting, such as in a familiar environment with unbiased conditions, which may lead to substantially better analysis and related treatment. According to embodiments of the present invention, a subject's gait can be quantitatively and objectively analyzed in a reproducible manner. In certain applications, for example, a therapist can determine in an objective and unbiased manner whether a patient has made progress.

[0029] Various other features and aspects of the invention are defined in the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which like parts are provided with corresponding reference numerals, and in which: Figure 1a A simplified schematic diagram of a system arranged according to certain embodiments of the present invention is provided; Figure 1b A simplified schematic diagram of a sensor module arranged according to certain embodiments of the present invention is provided; Figure 2 Provides a description Figure 1a A flowchart of the operation of the system shown in; Figure 3 A simplified schematic diagram of components of a sensor module for mounting to an article of footwear according to some embodiments of the present invention is provided; Figure 4A simplified schematic diagram is provided depicting sensors in a sensor unit according to some embodiments of the present invention; Figure 5 A simplified schematic diagram is provided depicting sensors in another sensor unit according to some embodiments of the present invention; Figure 6 provides diagrams depicting the location of vibration actuators according to certain embodiments of the present invention; Figure 7 A simplified schematic diagram is provided depicting the incorporation of a sensor module in an improved shoe sole according to some embodiments of the present invention; Figure 8 provides a simplified schematic diagram of components of another sensor module for mounting to an article of footwear, including, inter alia, a position tracking device, according to some embodiments of the present invention; and Figure 9a A simplified schematic diagram is provided depicting an embodiment of the invention in which a sensor module is incorporated into an article of footwear; and Figure 9b A simplified schematic diagram is provided depicting an embodiment of the invention in which a sensor module is incorporated into an article of footwear. Detailed Description

[0031] Figure 1a A schematic diagram of a system for providing intervention based on detected gait kinematics is provided, the system comprising a pair of articles of footwear 101 and a network arrangement N.

[0032] Footwear 101 comprises a pair of footwear articles provided by a pair of shoes 101 comprising a first shoe 101a and a second shoe 101b. Generally, first shoe 101a and second shoe 101b are identical except that they are configured to fit a right foot and a left foot, respectively, of a subject.

[0033] The sole 102 of each shoe 101a, 101b includes a cavity 103, and a sensor module 104 is installed in the cavity 103.

[0034] like Figure 1b As shown, 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 including a plurality of sensors.

[0035] The power supply unit 105 may be provided as a suitable rechargeable battery as known in the art. The battery may be charged by any suitable means, for example via a suitable power cable input interface or via an induction coil incorporated in the power supply for wireless charging.

[0036] The network arrangement N comprises a data network 110 a , a wireless base station 111 and a remote intervention system 112 via which the sensor module 104 is configured to transmit data to the remote intervention system 112 and optionally receive data from the remote intervention system 112 .

[0037] The remote intervention system 112 may include at least one electrical stimulation device, such as a deep brain stimulation device or a spinal stimulation device, configured to stimulate a region of the subject distal to the foot region.

[0038] Alternatively or additionally, the remote intervention system 112 may include a simulator, such as a virtual reality system (such as a system that provides a metaverse) and / or an augmented reality system, having a screen on which a video of the subject and / or simulated imagery of the subject may be displayed. The imagery may then be augmented by visual effects (e.g., visual effects of the metaverse or graphics that provide visual cues to the subject).

[0039] Generally, in the context of the claimed invention, an intervention is considered to be any form of feedback to a subject wearing footwear 101 or a third party such as a clinician to stimulate a response to the intervention in a desired manner by the subject. The intervention may be a sensory intervention such as: electrical stimulation, tactile intervention, visual intervention (such as an image on a display screen), or auditory intervention, etc. In the context of the described embodiments, a remote intervention is an intervention in an area away from the foot or feet of the subject wearing the footwear.

[0040] In some examples, the data network 110a may be provided by any suitable network for transmitting data between computing devices, such as the Internet. The wireless base station 111 may be provided by any suitable wireless access point compatible with the wireless communication unit 106 and adapted to enable data to be transmitted to and received from the data network 110a, such as a suitably connected Wi-Fi router. In alternative embodiments, the wireless base station 111 may be provided in a smartphone, similar mobile device, tablet computer, or any other device with suitable communication capabilities.

[0041] In use, for each sensor module 104 in each shoe, the plurality of sensors of the sensor unit 109 are configured to detect the motion of the subject while wearing the shoe and generate corresponding sensor data associated with the motion. Typically, the sensor data includes at least one or more of the following: linear acceleration data (generated by an accelerometer), angular velocity data (generated by a gyroscope), and orientation data (generated by a magnetometer).

[0042] The data processor 107a processes the sensor data to generate gait parameter data associated with the subject's gait kinematics. Figure 3 As shown, the data processor 107a has a gait characterization function 113 running thereon that is configured to process sensor data from the sensor modules of each shoe 101a, 101b to characterize aspects of the subject's gait kinematics.

[0043] The gait characterization function 113 implements one or more gait characterization algorithms that receive sensor data as input and generate therefrom gait parameter data associated with the subject's gait that can be derived from the sensor data. Techniques for converting such sensor data into gait parameter data are well known. For example, it is well known to use peaks, valleys, and zeros / crossings in sensor data generated by sensors that monitor human motion to identify "gait events," such as toe-offs and heel strikes.

[0044] Gait parameter data generated by one or more gait characterization algorithms may include data related to any one or any combination of more than one of the following: gait speed, step rate, step length, swing time variability, stride length, step width, rhythm (e.g., step time, swing time, stance time, single support, double support), variability (e.g., step rate variability, step length variability, step time variability, stance time variability), asymmetry (e.g., swing time asymmetry, step time asymmetry, stance time asymmetry), postural control (e.g., step length asymmetry), stride characteristics (strike angle, minimum toe clearance, foot angle (e.g., supination angle, strike angle, lift-off angle, angular velocity), peak parameters (e.g., peak propulsion force, peak braking), force / pressure values, and power. Gait parameters may also include one or more of load intensity and period and pressure distribution.

[0045] Then, the gait parameter data is transmitted by the wireless communication unit 106 to the remote intervention system 112 via the wireless base station 111 and the data network 110 a .

[0046] The remote intervention system 112 may also be configured to receive program parameters specified by the therapy program, movement assistance program, game program, or training program from a program parameter database 117 connected to the remote intervention system 112. These program parameters quantify how various aspects of the subject's gait kinematics will be altered from their normal motion if intervention is required.

[0047] Using one gait parameter, a combination of gait parameters, or all gait parameters and one or more program parameters specified by a therapy program, motion assistance program, gaming program, or training program, the remote intervention system 112 is configured to determine appropriate intervention based on the parameters specified by the therapy program, motion assistance program, gaming program, or training program.

[0048] For example, where the remote intervention system 112 includes an electrical stimulation device, such as a deep brain stimulation device or a spinal stimulation device, the intervention system 112 applies appropriate stimulation to the subject so that the subject responds in a desired manner.

[0049] Alternatively or additionally, the data processor 107a is configured to determine whether the determined gait parameters indicate a gait event. Figure 3 As shown, the data processor 107a may have a gait event prediction function 114 running thereon, which is configured to determine that the determined gait parameters correspond to a gait event, such as an impending fall, gait freezing, or deviation from expected motion.

[0050] If a gait event is determined, the data processor 107 a controls the wireless communication unit 106 to transmit gait parameter data associated with the gait event to the remote intervention system 112 .

[0051] For example, the gait event prediction function 114 can determine moving average data or moving variance data about one or more gait parameters based on the gait parameter data stored in the memory unit 107b. For example, the data processor 107a can be configured to periodically generate gait parameter data at predetermined intervals and store the generated gait parameter data in the memory unit 107b. The predetermined interval can be an interval suitable for the determined gait parameters. For example, gait parameter data can be periodically generated at predetermined intervals less than human reaction time, and the gait parameter data (e.g., gait stability) can be determined without completing a complete step / stride. For example, the interval can be less than 0.1 seconds. Gait parameter data (e.g., stride length) required to complete a complete stride / stride can be periodically generated at a predetermined interval (cadence) not less than the duration of the subject's stride / stride, or periodically generated at a predetermined interval (such as a predetermined interval of not less than 0.5 seconds and not more than 2 seconds, such as 1 second) not less than the duration of a typical stride / stride for a human to perform a particular movement (human movement cadence).

[0052] The determined gait parameters may then be compared to a moving average or moving variance to determine whether a gait event has occurred. If a gait event has occurred, the gait parameter data corresponding to the gait event is transmitted to the remote intervention system 112 to provide appropriate intervention.

[0053] In addition, the data processor 107a can control the vibration actuator 108 based on the determined gait parameters to provide appropriate stimulation to be applied to the subject's foot. It should be understood that in the case where intervention, particularly in the form of stimulation, is provided by the remote intervention system 112, any stimulation of the vibration actuator 108 may be unnecessary. Typically, the vibration is transmitted to the subject's foot via the middle portion of the sole that separates the vibration actuator 108 and the subject's foot.

[0054] In one example, the system may be used in a motion assistance program to generate appropriate reminder signals to reduce the likelihood of falls for elderly or other vulnerable subjects.

[0055] During use, the subject walks around wearing the shoe and corresponding sensor data is generated by the sensor.

[0056] The gait characterization function 113 uses the sensor data to generate gait parameter data related to the timing of the subject's gait swing as the subject walks (ie, the period of time it takes the subject to complete a stride).

[0057] The subject's swing time can generally be reliably determined using a simple algorithm. The swing time parameter may be generated by a gait characterization function 113 that identifies the time delay between the "toe-off" and "heel strike" events for each foot from the sensor data.

[0058] Specifically, based on 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 associated with the angular motion rate of the ankle.

[0059] Sensor data associated with a stride is typically characterized by two peaks, one near toe-off and heel-strike. Combining this information with sensor data associated with vertical acceleration (lift-off at toe-off and impact at heel-strike) enables the generation of real-time estimates of toe-off and heel-strike events.

[0060] The gait characterization function 113 is configured to generate swing time data (ie, gait parameter data) and then transmit the swing time data to the remote intervention system 112 by the wireless communication unit 106 .

[0061] In response to the received swing data, the remote intervention system 112 provides appropriate intervention. For example, the remote intervention system 112 may compare the received swing time data with swing time data stored in the program parameter database 117 (such as swing time data corresponding to normal movement of the subject) and determine that a fall is imminent.

[0062] Where the tele-intervention system 112 comprises an electrical stimulation device, such as a deep brain stimulation device or a spinal stimulation device, the tele-intervention system 112 then generates sensory stimulation to alert the subject that they may be about to fall and / or stimulate the subject's body to perform appropriate movements to prevent a fall.

[0063] Alternatively or additionally, 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.

[0064] Then, the gait characterization function 113 is configured to generate an average swing time value from the plurality of swing time values, the average swing time value being an average of the plurality of swing time values.

[0065] The gait characterization function 113 is further configured to use the plurality of swing time values ​​to calculate a time value corresponding to a standard deviation of the 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.

[0066] The data processor 107a has a gait event prediction function 114 running thereon, which is 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 impending fall. For example, the gait event prediction function 114 can be configured to determine whether the determined swing time data is within a predetermined number of standard deviations of the subject's average swing time, wherein if an impending fall is predicted, the subject's swing time will increase.

[0067] For example, the gait characterization function 113 may calculate from the sensor data that the average swing time of the subject is 700 ms, where the distribution of the swing times is such that one standard deviation relative to the average swing time is 250 ms. Therefore, the gait parameter data transmitted from the gait characterization function 113 to the gait event prediction function 114 will specify an average swing time value of 700 ms and a standard deviation time value corresponding to one standard deviation of 250 ms.

[0068] Additionally, program parameter database 117 may include program parameter data specifying that if a threshold increase in the subject's swing time of two deviations relative to the mean swing time is met or exceeded, this indicates an impending fall.

[0069] So in this example, this would be the gait swing time of at least: .

[0070] In such an example, the gait event prediction function 114 is configured to determine that a fall is imminent when the subject's swing time is 1200 ms or longer.

[0071] Therefore, when the subject's gait swing time changes to more than 1200 ms, the data processor 107a recognizes that the determined swing time exceeds the threshold gait swing time value, and transmits the swing time (i.e., gait parameter data) to the remote intervention system 112 via the wireless communication unit 106.

[0072] In response to the received swing time data, the remote intervention system 112 provides appropriate intervention. For example, where the remote intervention system 112 includes an electrical stimulation device (such as a deep brain stimulation device or a spinal stimulation device), the remote intervention system 112 generates sensory stimulation to alert the subject that they may be about to fall and / or stimulate the subject's body to perform appropriate movements to prevent the fall.

[0073] The data processor 107a can also generate a corresponding control signal, which, when received by the vibration actuator 108, causes the vibration actuator 108 to generate a corresponding sensory stimulus to remind the subject that they may fall. In this way, the reminded subject is less likely to fall.

[0074] The detection of sensor data associated with the swing time by the data processor 107a typically occurs at a rate higher than typical human reaction times. In this way, the subject experiences smooth and "instantaneous" feedback whenever a set threshold is exceeded, triggering intervention. Typically, human reaction times are around 0.1 s, and detecting the subject's gait swing time at 100 Hz will result in smooth operation.

[0075] In another example, the system may be used in a therapeutic procedure to help subjects who suffer from a neurological disease such as multiple sclerosis or Parkinson's disease and experience "freezing of gait."

[0076] In such an example, consistent with the previous example, the subject walks around wearing the shoes and corresponding sensor data is generated by the sensors.

[0077] Following the previous example, the gait characterization function 113 uses the sensor data to generate gait parameter data including a swing time gait parameter associated with the gait swing time of the subject when walking normally.

[0078] The gait characterization function 113 is configured to generate swing time data (ie, gait parameter data) and then transmit the swing time data to the remote intervention system 112 by the wireless communication unit 106 .

[0079] In response to the received swing data, the remote intervention system 112 provides appropriate intervention. For example, the remote intervention system 112 may compare the received swing time data with the swing time data stored in the program parameter database 117, such as the swing time data associating a decrease in average swing time exceeding a predetermined amount (e.g., 50%) within a predetermined time period (e.g., 60 seconds) with impending gait freezing, and determine that gait freezing is imminent.

[0080] In the event that the tele-intervention system 112 includes an electrical stimulation device, such as a deep brain stimulation device or a spinal stimulation device, the tele-intervention system 112 then generates sensory stimulation to alert the subject that they may be about to fall and / or stimulate the subject's body to perform appropriate movements to prevent impending gait freezing.

[0081] Alternatively or additionally, the memory unit 107 b may have stored therein program parameters specifying that a decrease in average swing time exceeding a predetermined amount (e.g., 50%) within a predetermined time period (e.g., 60 seconds) indicates an impending gait freezing. In the event that a decrease in the average swing time of the subject during a threshold time period (e.g., within 60 seconds) of at least a threshold amount (e.g., at least 50%) indicates an impending onset of gait freezing, the gait event prediction function 114 generates gait parameter event data indicating that a “gait freezing” is imminent, which is transmitted to the remote intervention system 112.

[0082] In response to receiving gait parameter event data indicating that "freezing of gait" is about to occur, intervention system 112 provides appropriate intervention. For example, where intervention system 112 includes an electrical stimulation device (such as a deep brain stimulation device or a spinal stimulation device), intervention system 112 generates sensory stimulation to alert the subject that they may be about to suffer an episode of freezing of gait and / or stimulate the subject's body to perform appropriate movements to prevent the onset of freezing of gait.

[0083] The data processor 107a may also generate a corresponding control signal, which, when received by the vibration actuator 108, causes the vibration actuator 108 to generate a corresponding sensory stimulus to remind the subject to start a step and end gait freezing. Thus, the reminded subject may be less likely to suffer from the onset of gait freezing.

[0084] In another example, the system may be used in a training program to assist a subject seeking to improve their technique when performing an activity such as running.

[0085] In such an example, in keeping with the previous example, the subject moves around wearing the shoes, and in particular moves around in a certain desired motion pattern. Corresponding sensor data is generated by the sensor.

[0086] The gait characterization function 113 uses the sensor data to generate gait parameter data indicative of one or more gait parameters associated with a desired movement pattern, such as step width and swing time.

[0087] The gait characterization function 113 is configured to generate swing time data and step width data (ie, gait parameter data) and then transmit the swing time data and step width data to the remote intervention system 112 via the wireless communication unit 106 .

[0088] In response to the received swing time data and step width data, the remote intervention system 112 provides appropriate intervention. For example, the remote intervention system 112 may compare the received swing time data and step width data with the swing time data and step width data stored in the program parameter database 117 to identify changes in the swing time and step width that are greater than 5% relative to the swing time data and step width specified by the sports training program stored in the program parameter database 117.

[0089] In the event that the tele-intervention system 112 includes an electrical stimulation device (such as a deep brain stimulation device, a spinal stimulation device, or a muscle stimulation device), the tele-intervention system 112 then generates sensory stimulation to alert the subject that the subject's movements deviate from the desired form and / or stimulate the subject's body to perform appropriate movements to correct the deviation.

[0090] Alternatively or additionally, the memory unit 107b may have stored therein program parameters associated with the movement training program, the program parameters specifying swing time data and step width data parameters with which the received swing time data and step width data are compared. In the event that the subject's received swing time data and step width data vary by more than 5% relative to the swing time data and step width data specified by the movement training program, indicating a deviation from the desired movement form, the gait event prediction function 114 generates form deviation gait event data, which is transmitted to the remote intervention system 112.

[0091] In response to the received form deviation gait event data, the intervention system 112 provides appropriate intervention. For example, where the intervention system 112 includes an electrical stimulation device (such as a deep brain stimulation device or a spinal stimulation device), the intervention system 112 generates sensory stimulation to alert the subject that they have deviated from the desired form and / or stimulate the subject's body to perform appropriate corrective movements.

[0092] The data processor 107a may also generate a corresponding control signal, which, when received by the vibration actuator 108, causes the vibration actuator 108 to generate a corresponding sensory stimulus to remind the subject to perform appropriate corrective movements.

[0093] However, in some examples, transmitting the form deviation gait event to the remote intervention system 112 causes the remote intervention system 112 to stop applying intervention. For example, the remote intervention system 112 can be configured to provide a conventional intervention according to a training program that conveys to a subject (such as an athlete) that they are moving at a desired speed. Upon determining that the subject has dropped below the speed or exceeded the speed, corresponding speed difference gait event data is generated and transmitted to the remote intervention system 112, and then the remote intervention system 112 stops providing conventional intervention until the desired speed is reached again.

[0094] As another example, the remote intervention system 112 may include an augmented reality (AR) system in which an image of a real-world environment is augmented by computer-generated sensory stimulation (e.g., visual stimulation such as images, auditory stimulation, or tactile stimulation) or a virtual reality (VR) system in which a virtual world is simulated. The AR system may include virtual objects that are spatially registered as objects within the image of the real-world environment. The virtual reality (VR) system may include a simulation (such as a metaverse) in which a subject is represented. In this context, the intervention provided by the remote intervention system including the AR / VR system is any sensory stimulation that can be experienced by a person, particularly a subject.

[0095] In the specific context of a system that may be used in a training program to assist a subject seeking to improve their technique when performing an activity such as running, the remote intervention system 112 includes an augmented reality (AR) system or a virtual reality (VR) system.

[0096] The gait characterization function 113 uses the sensor data obtained while the subject moves around using the shoe to generate gait parameter data indicative of one or more gait parameters associated with a desired form of movement.

[0097] The gait parameter data is then transmitted by the data processor 107a to the remote intervention system 112 via the wireless communication unit 106. The gait parameter data is then processed by the remote intervention system 112 to provide intervention in the form of sensory feedback (such as visual feedback), and the subject then responds to the intervention. For example, the visual feedback can be a virtual target that appears in front of the subject (or in front of the subject's representation) on the display of the AR / VR system and instructs the subject to follow. If it is determined that the subject's speed is too slow, the virtual target can be moved further away from the subject in the AR / VR system, thereby stimulating the subject to increase their speed. Alternatively or additionally, the visual feedback can be a modification of the virtual environment according to a predetermined training program. For example, the steps taken by the subject can be replicated in a virtual reality system (such as a metaverse).

[0098] The program parameters stored in the program parameter database 117 or the memory unit 107b are defined based on the type of program being provided (e.g., a training program, a therapy program, a game program, or a sports assistance program). In each case, the program parameters may be selected based on relevant research. For example, the program parameters for a therapy program that attempts to alleviate or reduce the occurrence of gait freezing will be defined based in part on what research on this condition has shown to be effective in treating this condition.

[0099] Program parameters may also be defined in part based on characteristics of the subject who will be using the system, such as, for example, characteristics such as age, weight, gender, height, etc. For example, in a program for providing motion assistance intended to reduce the likelihood of a fall in a subject, changes in swing time identified as predictive of an impending fall may vary based on the age of the subject.

[0100] Program parameters may also be defined in part based on historical data associated with a subject. For example, a particular subject may have previously exhibited a particular gait kinematics sequence prior to an episode of gait freezing. In such an example, program parameters may be selected to specify these gait kinematics.

[0101] Figure 2 A schematic diagram outlining one mode of operation of a system as described above is provided.

[0102] In a first stage S201 , sensor data is generated by a sensor of at least one shoe of a pair of shoes.

[0103] In a second stage S202 , the gait characterization function 113 processes the sensor data to generate gait parameter data associated with the subject's gait kinematics.

[0104] In a third stage S203 , the gait event prediction function 114 determines whether the gait parameter data indicates a gait event, and transmits the gait parameter data to the remote intervention system if the gait parameter data indicates a gait event.

[0105] In a fourth stage S204, in response to receiving the gait parameter data, the remote intervention system generates an intervention, to which the subject responds.

[0106] Advantageously, this means that a training program, movement assistance program or therapy program can continue to effectively adapt as the subject's gait kinematics change over time, for example due to changes brought about by the training program or therapy program.

[0107] Figure 3 A schematic diagram is provided that provides a more detailed view of a sensor module 104 arranged in accordance with certain embodiments of the present invention.

[0108] As can be seen, the sensor module 104 includes a power supply unit 105 , which in certain embodiments includes one or more rechargeable batteries 105 a and an inductive charging loop 105 b for charging the rechargeable batteries 105 a via a wireless charging unit.

[0109] The sensor module 104 also includes a data processor 107a, which may be provided as any suitable programmable microprocessor or other suitable data processing device, such as a custom designed integrated circuit, such as a field programmable gate array (FPGA).

[0110] The data processor 107a is connected to the motor power control circuit via a suitable signal line, which is connected to the vibration actuator 108 via another suitable signal line.

[0111] The vibration actuator is typically provided as an electric motor including a weight eccentrically mounted on the motor shaft. However, the vibration actuator may be provided as other suitable electromechanical devices, such as piezoelectric vibration actuators and voice coil-like linear electromagnetic actuators ("tactors").

[0112] The sensor unit 109 is connected to the data processor 107a via suitable signal lines. The sensor unit 109 is typically provided as an inertial measurement unit (IMU) comprising an accelerometer, a gyroscope and a magnetometer connected to the data processor unit.

[0113] The wireless communication unit 106 is also connected to the data processor 107a via a suitable signal line. The wireless communication unit 106 may be provided in any suitable wireless communication unit operating according to conventional radio 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 is provided with a subscriber identity module (SIM) and enables data to be transmitted to and from the data network 110a via a cellular mobile phone network.

[0114] All components of the sensor module 104 are connected to a power supply unit 105 via suitable power lines.

[0115] Figure 4 A schematic diagram is provided that depicts the sensors of the sensor unit 109 in more detail according to some embodiments of the present invention. Figure 4As can be seen, sensor unit 109 includes accelerometer 401, gyroscope 402, and magnetometer 403. This combination of sensors generally provides sufficient information about the subject's motion to enable characterization of various aspects of the subject's gait, including gait speed, pace, step length, swing time variability, stride length, step width, rhythm (e.g., stride time, swing time, stance time, single support, double support), variability (e.g., pace variability, step length variability, stride time variability, stance time variability), asymmetry (e.g., swing time asymmetry, stride time asymmetry, stance time asymmetry), postural control (e.g., step length asymmetry), stride characteristics (strike angle, minimum toe clearance, foot angles (e.g., supination angle, strike angle, lift-off angle, angular velocity), and peak parameters, such as peak propulsive force and peak braking.

[0116] In some embodiments, the sensor unit 109 may include one or more additional sensors.

[0117] Figure 5 A schematic diagram is provided depicting another example of a sensor unit 501 comprising Figure 4 The sensors of the sensor unit 109 are shown and include further sensors, specifically, a temperature sensor 502 , a sound sensor 503 , a foot pressure sensor 504 and an atmospheric pressure sensor 505 .

[0118] In use, the temperature sensor 502 is configured to measure temperature and generate corresponding temperature data. The temperature data is transmitted to the data processor 107a. The data processor 107a is configured to use the temperature data to calibrate the sensor data from the sensor unit 109 (if necessary) to account for changes (drift) in the output of the sensor unit 109 due to temperature changes to which the system is exposed.

[0119] In some examples, the data processor 107a is configured to process sensor data generated by the sound sensor 503, the foot pressure sensor 504, and the atmospheric pressure sensor 505 to generate gait parameter data.

[0120] In use, the foot pressure sensor 504 is usually positioned so that the pressure change caused by the subject contacting the ground can be detected. For example, the foot pressure sensor 504 can be provided by a two-dimensional pressure sensing pad, which is configured to be positioned across the bottom of the modified sole or a part of the bottom, so that when the subject's foot contacts the ground, the pressure at different contact points of the subject's foot can be measured. The foot pressure sensor 504 is configured to generate pressure data. The gait characterization function 113 is configured to use pressure data when generating gait parameters. For example, the gait characterization function 113 can use pressure data to determine the time point when the subject's foot contacts the ground and / or use pressure data to determine the time point when a specific area of ​​the subject's foot (such as the ball and heel) contacts the ground. Additional information related to analyzing the subject's gait can be determined from pressure data (such as the impact force of the subject contacting the ground with their feet or a specific area of ​​their feet).

[0121] In use, the 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 gait characterization function is configured to use the sound data to classify the type of surface on which the subject is moving (walking, running), which can then be used to refine the algorithm for estimating the subject's gait parameters. In some examples, the sound data can be used to detect the type or location of the subject's activity.

[0122] In use, the atmospheric pressure sensor 505 is configured to detect the atmospheric pressure around the shoe and generate corresponding atmospheric pressure sensor data. The atmospheric pressure sensor data can be used by the altitude detection function of the data processor 107a, which is configured to receive sensor data from the atmospheric pressure sensor to generate corresponding altitude data. The altitude data can be used to track the vertical movement of the subject while wearing the shoe, for example as part of an exercise program.

[0123] In certain embodiments, as described in more detail below, the altitude detection functionality may be incorporated into the motion distance analysis functionality.

[0124] The skilled person will appreciate that the arrangement of components of the system is one example of how a system according to an embodiment of the invention may be arranged and that components of the system may be represented in any suitable alternative manner.

[0125] For example, in other configurations, the intervention system may include a personal computing device, such as a personal computer ("PC"), tablet computer, smartphone, or similar device, and the program parameters are stored in a suitable memory on such a device.

[0126] In some embodiments, each sensor module and the remote intervention system may communicate directly via a suitable data link, i.e., without requiring a remote intervention system to communicate directly with the sensor module. Figure 1a The intermediate data network shown and / or the absence of an intermediate base station. For example, the remote intervention system and each sensor module may communicate data to each other via a short-range radio protocol such as Bluetooth, WiFi or the like.

[0127] In embodiments of the invention, the sensor module may be configured to stimulate (by virtue of the positioning of the vibration actuator relative to the sole of the article of footwear) any suitable area on the plantar (underside) of the subject's foot (the sole of the foot).

[0128] These areas include the first metatarsophalangeal joint; the fifth metatarsophalangeal joint, the heel area; the area of ​​the big toe and the medial longitudinal arch. These example areas are Figure 6 In the example where the article of footwear incorporates a single vibration actuator, the actuator may be positioned in any one location, but the skilled person will recognize that Figure 6 Other positions not shown are also possible.

[0129] In some examples, each article of footwear may be provided with more than one vibration actuator. In such examples, the sensor module may be configured so that the vibration actuators are positioned to provide sensory stimulation to any suitable combination of regions of the sole of the subject's foot. For example, a first vibration actuator may be positioned to stimulate a foot position in the first metatarsophalangeal joint region; a second vibration actuator may be positioned to stimulate a foot position in the fifth metatarsophalangeal joint region, and a third vibration actuator may be positioned to stimulate a foot position in the heel region. In some other embodiments, a fourth vibration actuator may be positioned to stimulate a foot position in the big toe region.

[0130] In certain embodiments, the number of vibration actuators and the locations of the vibration actuators will be selected based on the type of therapy or training being delivered to the subject, for example because stimulation in different locations may induce different responses in different patient groups.

[0131] In the example above, the foot stimulation vibration may be "sensory" such that the subject is consciously aware of the vibration. This is an example of a "tactile cue" whereby the subject receives a "cue" through a consciously perceptible tactile stimulation.

[0132] However, in some examples, such as where vibrations are applied as a treatment for, for example, diabetic neuropathy patients, or for preventing falls or in response to foot freezing, the vibrations may be subsensory, such that the subject may not be consciously aware of the vibrations, but the vibrations still generate neural stimulation and produce the desired effect, such as improved balance and walking. In such examples, the foot stimulation vibrations generated by the one or more vibration actuators are subsensory vibrations (not consciously perceptible by the subject).

[0133] In particular, in the example of generating sub-sensory vibrations, a data processor associated with each article of footwear may be configured to calibrate the vibrations generated by the vibration actuator (or each vibration actuator) to account for the fact that different subjects have different sensory threshold levels and that these sensory thresholds will vary between different areas of the subject's foot.

[0134] To facilitate this, the data processor associated with each article of footwear may be configured to implement a calibration process that controls the vibration actuator (or each vibration actuator) to iteratively step through a sequence of different vibration levels until a vibration level is identified that is just below the subject's sensory perception of the vibration actuator stimulating the subject's foot region. This calibration process may be performed in conjunction with an external device (e.g., a mobile computing device, such as a smartphone) connected to the data processor via a data transceiver and a suitable wireless link.

[0135] The different vibration levels may be provided by a vibration actuator that vibrates at different frequencies (e.g., when the vibration actuator is provided as an electric motor including a weight eccentrically mounted on a motor shaft) and / or a vibration actuator that vibrates at different amplitudes (e.g., when the vibration actuator is provided as a voice coil-like linear electromagnetic actuator ("haptic")).

[0136] In this manner, after the calibration process is complete, a vibration level (typically including vibration frequency and / or vibration amplitude) will be determined for each vibration actuator and then used during system operation.

[0137] In some examples, a data processor in each article of footwear controls a vibration actuator (or each vibration actuator) to generate foot stimulating vibrations using "stochastic resonance". In such examples, the foot stimulating vibrations are generated according to a random pattern (which is generally more effective for neural stimulation). For example, the vibration actuator can be configured to apply the foot stimulating vibrations in an "on / off" pattern, where the time between the "on" phase and the "off" phase varies randomly between, for example, 0.01 seconds and 0.09 seconds.

[0138] In some examples, sensory stimulation devices according to embodiments of the present invention may be incorporated into a modified insole that can be inserted into and removed from an article of footwear. Examples of such embodiments are Figure 7 shown. Figure 7 A simplified schematic diagram is provided showing an otherwise conventional article of footwear 701 including a sole 702 and an upper 703 (sole 702 and upper 703 are shown in phantom and transparent). A removable modified insole 704 is shown, into which an assembly 705 including a vibration generating device is incorporated.

[0139] As will be appreciated, removable modified insole 704 can be removed from article of footwear 701 and placed in a different article of footwear. This allows, for example, modified insole 704 to be used in footwear of multiple subjects or multiple articles of footwear of the same subject. Modified insole 704 can include a washable and / or otherwise sterilizable outer layer, which enables modified insole 704 to be cleaned, for example, for hygienic purposes after use in footwear of a first subject and before use in footwear of a second subject.

[0140] In reference Figure 1a In the described examples, all components associated with detecting the subject's motion and applying sensory stimulation are combined in a single sensory stimulation unit. However, in other examples, these components can be integrated with the footwear in different ways. For example, one or more vibration actuators can be mounted on a modified sole or a modified insole, while other components, such as sensors and data processors, can be incorporated into other components of the footwear, such as, for example, an upper or a tongue.

[0141] Embodiments of the present invention may be used with any suitable form of footwear. Such footwear includes shoes such as trainers (sneakers), boots, and sandals. In certain embodiments, the vibration generating device may be incorporated into specific medical footwear, such as a controlled ankle motion (CAM) walking boot ("moon boot").

[0142] In some embodiments, the sensor module of one or both shoes is configured to implement a movement distance tracking function. The movement distance tracking function is configured to track the distance that the shoe has moved and generate corresponding movement distance data.

[0143] The motion distance analysis function can be configured to analyze the motion distance data to determine the motion pattern associated with the movement of the shoe (e.g., total movement distance, average movement time, maximum and minimum movement distances within a set time period, etc.), and generate corresponding motion distance analysis data. The motion distance analysis data can then be used to optimize the treatment program, sports assistance program, game program, or training program provided by the system. For example, an expert (e.g., a doctor) can manually change the program parameters stored in the program parameter database based on the subject's motion distance pattern.

[0144] The motion distance tracking function can be implemented by any suitable means. For example, the motion distance tracking function can be implemented on a data processor on a sensor module of one or both shoes, and the sensor module can be further equipped with 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 thereby generate motion distance data. In other examples, the motion tracking function can be configured to use sensor data collected by the sensor unit (e.g., by estimating the number of steps taken by the subject to infer the total distance moved) and thereby generate motion distance data.

[0145] Figure 8 A schematic diagram of a sensor module arranged for this purpose is provided. Figure 8 Shown is the reference Figure 3 A sensor module is that of the described sensor module, except that it also includes a position tracking device 801 provided by a GNSS receiver such as a GPS receiver.

[0146] As described above, in some embodiments, the movement distance analysis function can be combined with the altitude detection function, so that when generating the movement distance analysis data, the movement patterns associated with the altitude (e.g., the number of meters ascended and / or descended in a given time period) can also be considered.

[0147] In certain embodiments, the system is provided with additional functionality, enabling sensory stimulation to be generated for additional purposes.

[0148] For example, in some embodiments, the system is configured to provide tactile cues to prompt the subject during training or testing.

[0149] Such prompts may include prompting the subject to perform actions such as start, stop, turn around, sit down, stand up, etc.

[0150] Such embodiments may be implemented in any suitable way.

[0151] The data processor of the sensor unit has a tactile cue generation function running thereon.

[0152] In this way, for example, during training or therapy, a sequence of tactile cue vibrations can be generated that prompts the subject to start walking, then stop walking, then start walking again, and so on.

[0153] In the example embodiments described above, the vibration actuators of the sensor module are positioned and configured so that sensory stimulation is applied primarily to the plantar (underside) of the subject's foot, ie, the sole of the subject's foot.

[0154] However, in other embodiments, the sensor module may alternatively or additionally be configured to apply sensory stimulation to other areas of the subject's foot. For example, in some embodiments, an article of footwear is provided that incorporates a sensor module that substantially corresponds to those described above, except that one or more vibration actuators of the sensor module are positioned and configured to apply sensory stimulation to the subject's ankle or an area proximate to the subject's ankle.

[0155] Figure 9a A simplified schematic diagram of such an embodiment is provided. Figure 9a A sensor module 902 of the type described above and including, for example, Figure 3 Article of footwear 901a having all the components depicted in FIG. Figure 9a As can be seen, sensor module 902 is mounted to article of footwear 901a in a position such that sensory stimulation will be applied distal to the subject's ankle during use.

[0156] In additional embodiments, an article of footwear is provided that incorporates a sensor module substantially corresponding to those described above, except that one or more vibration actuators of the sensor module are positioned and configured to apply sensory stimulation to the instep (upper side) of a subject's foot.

[0157] Figure 9b A simplified schematic diagram of such an embodiment is provided. Figure 9b A sensor module 903 of the type described above and including e.g. Figure 3 Article of footwear 901b having all the components depicted in FIG. Figure 9b As can be seen, sensor module 902 is mounted to article of footwear 901a in a position such that, during use, sensory stimulation will be applied to the instep (upper side) of the subject's foot.

[0158] All features disclosed in this specification (including any accompanying claims, abstracts and drawings), and / or all steps of any method or process so disclosed, may be combined in any combination, except combinations in which at least some of such features and / or steps are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including any accompanying claims, abstracts and drawings) may be replaced by an alternative feature serving the same, equivalent or similar purpose. Therefore, unless expressly stated otherwise, each feature disclosed is merely an example of a general series of equivalent or similar features. The invention is not limited to the details of the foregoing embodiments. The invention extends to any novel feature or novel combination of any features disclosed in this specification (including any accompanying claims, abstracts and drawings), or any novel step or novel combination of any method or process so disclosed.

[0159] With respect to the use of substantially any plural and / or singular terms herein, those skilled in the art may convert the plural to the singular and / or the singular to the plural as appropriate to the circumstances and / or application. For clarity, various singular / plural permutations may be expressly set forth herein.

[0160] Those skilled in the art will understand that, in general, the terms used herein, and especially in the appended claims, are generally intended to be "open" terms (e.g., the term "including" should be interpreted as "including but not limited to," the term "having" should be interpreted as "having at least," the term "comprising" should be interpreted as "including but not limited to," etc.). Those skilled in the art will further understand that if a specific number of claim references are intended to be introduced, such an intent will be explicitly referenced in the claim, and in the absence of such reference, no such intent is present. For example, to aid understanding, the following appended claims may contain usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However, the use of such phrases should not be construed to imply that a claim reference introduced by the indefinite article "a" or "an" limits any particular claim containing such introduced claim reference to embodiments containing only one such reference, even when the same claim includes the introductory phrases "one or more" or "at least one" and an indefinite article, such as "a" or "an" (e.g., "a" and / or "an" should be construed as "at least one" or "one or more"); this is also true when the definite article used to introduce the claim reference is used. In addition, even if a specific number of introduced claim references is expressly referenced, one skilled in the art will recognize that such reference should be construed to mean at least the cited number (e.g., the simple reference in "two references," without other modifiers, means at least two references, or two or more references).

[0161] It will be understood that various embodiments of the present disclosure have been described herein for illustrative purposes and that various modifications may be made without departing from the scope of the present disclosure. Therefore, the various embodiments disclosed herein are not intended to be limiting, with the true scope being indicated by the appended claims.

Claims

1. A system for providing intervention based on detected gait kinematics for treatment, training, gaming or sports assistance, the system comprising: at least one article of footwear incorporating one or more sensors, 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 article of footwear, wherein: The one or more sensors are configured to generate sensor data associated with movement of the subject; The data processor is configured to process the sensor data to generate gait parameter data associated with gait kinematics of the subject, and, The wireless communication unit is configured to transmit the gait parameter data to the remote intervention 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 or 2, wherein: The remote intervention system comprises at least one stimulation device, such as a spinal stimulation device or a deep brain stimulation device or a muscle stimulation device.

4. The system according to any one of claims 1 to 3, wherein: The remote intervention system includes a simulator, such as a virtual reality system or an augmented reality system.

5. The system of any one of the preceding claims, wherein the at least one article of footwear further comprises a memory, wherein: The memory is configured to store sensor data and / or gait parameter data.

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

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

8. The system according to claim 6 or 7, wherein: The gait event is at least one of: an impending fall or a higher risk of falling by the subject, an impending freezing of gait or a higher risk of freezing of gait, a deviation from the subject's desired movement, and maintaining the subject's desired movement form.

9. A system according to any one of claims 5 to 8, wherein: The data processor is configured to periodically generate gait parameter data at predetermined intervals and store the generated gait parameter data in the memory.

10. A system according to any one of the preceding claims, wherein: The gait parameter data includes data related to one or more of the following items: gait speed, stride speed / stride speed, step length / stride length, swing time variability, stride length, stride duration, step width / stride width, rhythm, variability, asymmetry, posture control, step characteristics, cadence, gait rate, swing-support ratio, heel-off, toe-off, heel strike, full-foot landing events, gait variability and gait stability.

11. A system according to any one of the preceding claims, wherein: The one or more sensors, the data processor, the memory, and the wireless communication unit are embedded in a sole or insole of the article of footwear.

12. A system according to any one of the preceding claims, wherein: The sensor includes one or more inertial measurement units including one or more of an accelerometer, a gyroscope, and a magnetometer.

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 contacting the ground, a temperature sensor for detecting ambient temperature, an atmospheric pressure sensor for detecting atmospheric pressure, and a sound sensor.

14. A system according to any one of the preceding claims, wherein: The at least one article of footwear further includes a movement distance tracking device configured to generate movement distance data associated with a distance moved by the article of footwear, and the data processor is configured to process the movement distance data to generate movement distance analysis data.

15. The system of claim 14, wherein: The wireless communication unit is configured to transmit the motion distance analysis data to the remote intervention system.

16. A system according to any one of the preceding claims, wherein: The at least one article of footwear includes a rechargeable battery for powering components incorporated into the at least one article of footwear.

17. A method of providing intervention based on detected gait kinematics for treatment, training, gaming or sports assistance, the method comprising: generating sensor data at an article of footwear associated with movement of a subject wearing the article of footwear; at the article of footwear, processing sensor data to generate gait parameter data associated with gait kinematics of the subject; transmitting the gait parameter data from the article of footwear to a remote intervention system for providing intervention, and The remote intervention system is controlled to provide an intervention for eliciting a response from a subject wearing the article of footwear.

18. A device for fitting to an article of footwear, the device comprising one or more sensors, a data processor, and a wireless communication unit, wherein: The one or more sensors are configured to generate sensor data associated with movement of a subject wearing the article of footwear; The data processor is configured to process the sensor data to generate gait parameter data associated with the subject's gait kinematics, and The wireless communication unit is configured to transmit the gait parameter data to a remote intervention system.

19. An article of footwear having the device according to claim 18 mounted thereon.

20. A pair of footwear comprising a left-hand article of footwear according to claim 19 and a right-hand article of footwear according to claim 19.

21. A computer program for running on a data processor incorporated in an article of footwear and for use in a system according to claim 1, the computer program comprising instructions which, when implemented on a data processor, control the data processor to perform a method comprising: generating sensor data at an article of footwear associated with movement of a subject wearing the article of footwear; at the article of footwear, processing sensor data to generate gait parameter data associated with gait kinematics of the subject; and The gait parameter data is transmitted from the article of footwear to a remote intervention system for use in providing an intervention that elicits a response from a subject wearing the article of footwear.

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