WEARABLE POSITION TRAINING SYSTEM

Abstract

A wearable system for correction of body position, the system includes: a position sensor, configured to detect a position of a user's body part, and to transmit a position signal corresponding to the detected position; a processor, configured to receive the position signal, and to determine a deviation of the detected position from a predetermined optimal position; and a tactile feedback unit, configured to generate a tactile output in response to a determination that the detected position deviates from the optimal position by equal to or more than a threshold deviation. A method of correcting a user's body position includes the steps of: detecting, by a position sensor, the position of a body part of a user; transmitting a signal corresponding to the detected position; determining, by a processor, a deviation of the detected position from a predetermined optimal position; and generating, by a tactile feedback unit, a tactile output in response to a determination that the detected position deviates from the optimal position by equal to or more than a threshold deviation.

Claims

1. A wearable system for correction of body position, the system including: a sensor, configured to detect a position of a user's body part or a movement pattern of a user's body part, and to transmit a signal corresponding to the detected position or detected movement pattern; a processor, configured to receive the signal, and to determine a deviation of either the detected position from a predetermined optimal position, or the deviation of the detected movement pattern from a predetermined optimal movement pattern; and a tactile feedback unit, configured to generate a tactile output in response to a determination that the detected position deviates from the optimal position or optimal movement pattern by equal to or more than a threshold deviation.

2. A wearable system according to claim 1, wherein the sensor is wearable, and includes an attachment means for attaching to the body part in question.

3. A wearable system according to claim 1 or claim 2, wherein the sensor is a position sensor, and is configured to detect the position of the body part in question based on its own position.

4. A wearable system according to any one of the preceding claims, wherein the sensor includes one or more of: a gyroscope, an accelerometer and a magnetometer.

5. A wearable system according to any one of the preceding claims, wherein the sensor is configured to continuously monitor the position or movement pattern of the body part in question.

6. A wearable system according to any one of the preceding claims, wherein the processor is configured to generate a deviation signal on determining that the detected position or movement pattern deviates from the optimal position or optimal movement pattern by equal to or more than the threshold deviation.

7. A wearable system according to any one of the preceding claims, wherein the processor is configured to transmit the deviation signal to the tactile feedback unit, and the tactile feedback unit is configured to receive the deviation signal.

8. A wearable system according to any one of the preceding claims, wherein the tactile feedback unit is configured to generate the tactile output in response to receiving the deviation signal.

9. A wearable system according to any one of the preceding claims, wherein the sensor, the processor and the tactile feedback unit are located within a single component.

10. A wearable system according to any one of the preceding claims, further including a garment, wherein one or more of the sensor, the processor, the single component and the tactile feedback unit is attached to the garment.

11. A wearable system according to any one of the preceding claims, wherein the garment is one of the following: trousers, a jacket, a shirt, shoes, shoe inlays or gloves.

12. A wearable system according to any one of the preceding claims, wherein the tactile feedback unit includes one or more vibrators, and wherein the tactile output of the tactile feedback unit is in the form of a vibration.

13. A wearable system according to any one of the preceding claims, wherein the nature of the tactile output varies with the extent of the deviation.

14. A wearable system according to any one of the preceding claims, wherein the tactile feedback unit is configured to provide the tactile output to locations in the body where the response is intuitive.

15. A wearable system according to any one of the preceding claims, wherein the tactile feedback unit is configured to provide the tactile output to one or more of: the base of the chin, the base of the back of the head, the area of chest covering the backbone, the front of the shoulder, between the shoulder blades, the outside of the elbow, above the waist, above the navel, or the inside of the hand.

16. A wearable system according to any one of the preceding claims, including a plurality of sensors and a corresponding plurality of tactile feedback units.

17. A wearable system according to any one of the preceding claims, wherein each of the plurality of sensors is configured to transmit a respective signal to a single processor, and the single processor is configured to transmit a deviation signal to each of the plurality of tactile feedback units.

18. A wearable system according to any one of the preceding claims, including a plurality of modules, each including a sensor and a tactile feedback located within the same housing.

19. A wearable system according to any one of the preceding claims, further including one or more pressure sensors or force sensors arranged to detect a pressure distribution or force distribution of the user over an area, and to transmit a pressure signal or force signal to the processor.

20. A wearable system according to any one of the preceding claims, wherein the processor is configured to determine the deviation signal based on the pressure signal or force signal and the signal corresponding to the detected position or detected movement pattern.

21. A wearable system according to claim 19 or claim 20, wherein the system includes a force sensor located between a stirrup and a stirrup leather.

22. A wearable system according to any one of the preceding claims, wherein the threshold deviation is adjustable by a user.

23. A wearable system according to any one of the preceding claims, wherein the system further includes a computer system configured to receive an input from a user.

24. A wearable system according to claim 23, wherein the computer system has loaded thereon an application configured to provide a user interface, the computer system configured to receive the input from the user via the user interface.

25. A wearable system according to claim 23 or claim 24, wherein the processor is located on or in the computer system.

26. A wearable system according to any one of the preceding claims, wherein the system further includes a memory, in which the system is configured to store position data and/or movement pattern data from the sensor or sensors.

27. A wearable system according to any one of the preceding claims, wherein the tactile feedback unit is configured to generate a tactile output only when it is determined that the user is performing a selected activity.

28. A wearable system according to claim 27, wherein the selected activity has associated with it an activity model, which defines the set of movements associated with that activity, and wherein the processor is configured to compare position data and/or movement pattern data from the sensors with the activity model in order to determine whether or not the position data and/or movement pattern data is consistent with the selected activity.

29. A wearable system according to claim 28, wherein the processor is also configured to update the activity model based on the data from the sensors.

30. A wearable system according to claim 28 or claim 29, wherein the activity model is stored on the memory.

31. A wearable system according to any one of the preceding claims, wherein the user is a horse rider, and the system is configured to identify the gait of the horse.

32. A method of correcting a user's body position, the method including the steps of: detecting, by a sensor, the position of a body part of a user or the movement pattern of a body part of a user; transmitting a signal corresponding to the detected position or movement pattern; determining, by a processor, a deviation of the detected position or movement pattern from a predetermined optimal position or optimal movement pattern; and generating, by a tactile feedback unit, a tactile output in response to a determination that the detected position or movement pattern deviates from the optimal position or optimal movement pattern by equal to or more than a threshold deviation.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Embodiments of the invention will now be described in detail with references to the accompanying drawings, in which:

[0059] FIG. 1A shows a schematic overview of a system of the present invention.

[0060] FIGS. 2A to 2C show examples of the placement of various sensors and tactile feedback units according to the present invention.

[0061] FIGS. 3A to 3C illustrate some of the machine learning algorithms which may be performed according to the present invention.

[0062] FIG. 4 illustrates the z-direction movement associated with a variety of types of horse gait.

DETAILED DESCRIPTION OF THE DRAWINGS

[0063] Broadly speaking, preferred embodiments of the invention are directed towards a wearable system for reinforced learning to immediately and intuitively adjust different body parts positioning to a desired position for different activities like sport, work positions or rehab purposes by delivering a tactile feedback on specific points. The system helps improve the muscle memory by inducing intuitive tactile feedback in real time. More specifically, the system is capable of providing intuitive feedback in real time on the body part that is to be corrected while performing an activity. The units are fastened directly on the body part they intend to influence and are able to communicate with each other. The system is optimized with the help of machine learning algorithms and the collected data to deliver a more and more optimized feedback for the user over time.

[0064] FIG. 1 shows a broad overview of the system 100 in one embodiment of the present invention. Broadly speaking, the system 100 is divided into two parts: the unit 102 and the external device 104. These will be discussed in turn below. The unit 102 includes sensor 106, CPU/memory module 108, output 110, wireless component 112, and power supply 114. The operation of the system 100 will now be described. Sensor 106 is a position sensor as discussed earlier on in the application. It is worn by, or attached to a user of the device (locations of the position sensors are discussed in more detail later on with reference to FIGS. 2A to 2C), and is configured to detect the position of the body part to which it is attached.

[0065] This may, for example, be the chin of a user. The sensor 106 may be self-calibrated before operation, as discussed earlier in the application. On detection of the user's position, the sensor 106 is configured to transmit a position signal to the CPU/memory module 108, which is equivalent to the processor as discussed earlier in the application. The CPU of the CPU/memory module 108 then determines the deviation in the user's position from a predetermined optimal position. In the event that the deviation is greater than a predetermined threshold deviation, the CPU/memory module 108 is configured to send a signal to the output 110, i.e. the tactile feedback unit. On receipt of that signal, the output 110 generates a tactile output, such as a vibration, to inform the user that they have deviated too far from an optimal position. The sensor 106, the CPU/memory module 108, and the output 110 all receive power from the power supply 114.

[0066] In addition to providing real-time feedback via the output 110, the system 100 is also configured to record and store data concerning a user's position as they use the system 100. To that end, the memory portion of the CPU/memory module 108 may store data from the position sensor 106. In preferred embodiments, the memory is a temporary store. The unit 102 includes a wireless component 112, which is able to transmit signals wirelessly, e.g. by Bluetooth or RF signals to the external device 104. Specifically, the external device 104 may include a user interface device 116, in the form of e.g. a phone, a tablet or a computer. Data stored in the memory of the CPU/memory module 108 of the unit 102 may be transmitted using the wireless unit 112 to the user interface device, from which it may then be transmitted by the user interface device 116 to an external server or cloud server 118 for permanent storage. The user interface device 116 may also connect to other units 120 identical to unit 102.

[0067] As described in more detail in the Summary section of this application, the user interface device 116 preferably has loaded on it an application which the user may use to adjust various parameters associated with the invention.

[0068] FIG. 2A shows frontal, rear and side views of possible locations in which units (i.e. a combination of position sensors 106 and tactile feedback units 112) may be placed on the user's body: [0069] Sensor 200 is located under the user's chin. A tactile output applied here causes the user to intuitively lift their head. [0070] Sensor 202 is located on the chest in the region of the breastbone. A tactile output here can be used to correct intuitively a user's slouching with their upper body and chest. [0071] Sensors 204a, 204b are located at the front of the user's shoulders. A tactile output here is used to correct intuitively a shoulder that has fallen forward. [0072] Sensors 206a, 206b are located on the user's hands, specifically in the location indicated in FIG. 2C. In doing so, undesirable twisting of the user's hands can be corrected intuitively, in order to ensure that the hand is in the optimum position, with the thumb on top. [0073] Sensors 208a, 208b, 210 are located on the user's waist and stomach. These can be used to correct intuitively position of the user's waist, i.e. their seat position. Specifically, sensors 208a, 208b, on the sides of the body, in the area above the waist are used to compare symmetry and to detect whether the user might bend at the waist on one side, most riders do. Sensor 210, a few inches above the belly button is used to entice the user to engage the core, which stabilizes and balances the whole trunk). [0074] Sensor 212 is located at the back of the user's head, and can be used to cause a user to intuitively pull their head back and tuck their chin in, in order to correct a position in which the head is too far forwards. [0075] Sensor 214 is located in the user's upper back (and will entice the user to pull their shoulder blades back, in contrast to the ones in the front that lift the breastbone. More tension is usually caused by this feedback but in some cases it is preferred. [0076] Sensors 216a, 216b are located at the outside of the user's elbows, to help the user position the elbows next to the body. Most riders have a tendency to stretch their arms forward, creating tension and stiffness in the movement of the arm and hand. In the correct position the arms should be bent at the elbow, placed naturally hanging down on the side of the body, and from the elbow to the horse's mouth should be a straight line. The signal to the horse is not mainly given by moving the arms around but mainly controlled with the tension of the muscles in the back. These will control the contact the rider has with the horse's mouth. If the arms are held in front of you or this line is broken you have to use your arms to change this pressure which is incorrect.)

[0077] By intuitively it should be understood that the user moves the relevant body part in the right direction to correct the perceived deficiency, and by the right amount.

[0078] The shades areas are representing areas where there are pressure sensors that will deliver an output in the shape of a pressure pattern or a specific value. This pattern is compared to an optimal pattern and the value is compared between the two sides, in most instances, but not always, the value should be similar on the two different sides.

[0079] The area 318 around the crotch and the backside, are the area where the pressure of the pelvis is measured when the rider is sitting in the saddle. Points 308a, 308b are where the tactile feedback is applied to inform the user to move the rotation of the pelvis forward or backward, or the weight of the body right or left to have an equal weight distribution.

[0080] The areas 314a, 314b, on the inside leg is the areas where the thigh encloses the horse. The correct value is when the weight is evenly spread over the whole area and has contact. It is easy that the rider loses contact on one leg or parts of the area and then feedback is given feedback at points 302a, 302b.

[0081] The area 316 under the ball of the foot is where the stirrup is placed and once again this should be evenly distributed over the area and similar on both sides, since the correct stance is very similar to a standing position. If it is not the user need to correct the legs position and/or the weight distribution between sides. The points 304a, 304b, 310a, 310b on the ankles and heels are areas where feedback is given to move the leg back or forward.

[0082] Inside the hand on the fingers next to the palm the pressure are compares the pressure between the two hands since in most instances, if you are not on a bent track, the pressure of both hands should be the same to have an even pressure of the bit in the horse's mouth. If it is not this with be signalled to the user in the feedback point inside the hand by a certain pattern, different from the rotation of the hand feedback.

[0083] As is discussed earlier in this application, preferable embodiments of this invention are able to use machine learning techniques in order to improve the quality of the feedback which is given to a user when using the system 100. FIGS. 3A to 3C illustrate this process. The specific examples shown in these drawings are directed towards the use of the system by a horse rider, but the skilled person is well-aware that it may be used during other sports and activities, where the gait detection loop is replaced with one consistent with the specific parameters of said activity.

[0084] When a user first starts using the system, there are certain out of the box settings, i.e. default settings which are automatically in place. However, there is also an option for the user to create a specific account, which is assigned a prefix. Each time the user uses the device it gathers raw data that is stored under this prefix on a server or in the cloud (or temporarily on the device internal memory in CPU/memory unit 108). The prefix could be the user's name. In some embodiments, the prefix value could be the name of a specific horse. The same user might have several accounts if they have several horses. Each session the rider logs into their account all the raw data received by the position sensors (and/or pressure sensors in those embodiments which include them) is collected, and used to determine and classify patterns.

[0085] Algorithms are used in order to determine what movement is within the set of desired movements and what movements are undesired or noise. Here, desired movements refers to those movements which are associated with the activity in question, whereas noise represents those movements which are result from other events. The set of desired movements may be referred to as the optimal body pattern (OPB), which is a predetermined desired movement pattern for a specific body part for a given activity.

[0086] The OPB may be determined as follows: there is a normal range of movement for each body part movement when a given activity is performed. This normal range may be determined by position; i.e. by the position sensors, pressure distribution and over time. This normal range is determined by gathering raw data from a large number of expert users that have been performing the movement/activity while being filmed. Each deviation is supplied with a timestamp that has been used to create a model from the raw data of the normal range of this movement in terms of position and duration. Thus, an OBP may be determined for each body part.

[0087] Using an application on the user interface device 116, the user is able to control, adjust or tweak the OBP based on their individual preferences. The adjustment may take place based on one or more of the following criteria: skill level/acceptable deviation from optimal value, acceptable time delay, (acceptable duration for which the body part in question can deviate from the optimal position by equal to or greater than the threshold deviation), form of tactile output (strength, duration, intensity, pattern or and in some cases it may be turned off entirely, so the system is configured only to collect data), priority if using several units and time-delay in between signals from a plurality of units.

[0088] FIGS. 3B and 3C show two machine learning loops which the processor 108, or other component of the system 100 is configured to perform. By using these loops, it is possible to optimize when a tactile output signal should be delivered, and also to evolve the OBP for future iterations of the system. Specifically, the loops are used to: [0089] Determine that a user is actually performing the intended activity, and so that feedback should be given. [0090] Determine the gait of the horse in order to optimize the functioning of the system. In the case of other activity then horse riding this loop will be replaced by one with specific parameters for that activity.

[0091] FIG. 3B represents the first of these. Since the OBP of each body part for a given activity is predetermined, there exists already a predetermined range over which feedback can be delivered.

[0092] Data is collected to identify the user's and other movement patterns, to determine whether the activity is within the scope of the specified movement for the body part. This is done in order to allow the system to establish whether the user is engaged in the activity for which feedback is desired. Patterns over time may be identified, which will show when the user is performing an activity for which feedback is not required (i.e. in which they are not required to adopt the vertical seat position, discussed at the beginning of this application). Such activities may include: running, walking, standing still, talking, mounting the horse, bending down, falling off the horse, jumping an obstacle, riding over cavaletti, or the like

[0093] The raw data that is collected from each user is analysed by the system in order to identify repeating patterns in the data during the duration of each use. For example, the user may switch the system on, and select their preferred settings while standing still on the ground. There may or may not be a time delay before they mount the horse. What this mounting pattern looks like will clearly differ between users, however, there will be some similarities between the mounting patterns of all users. So, by collecting a large amount of data, it is possible to more clearly recognize, differentiate, and label movement patterns. This then means that adjustments can be made to the system based on the activity which is identified.

[0094] In another example, a rider may have fallen off the horse, and be lying still on the ground. Clearly, at this point, feedback about the rider's body position is not especially important.

[0095] So, the system will identify that the activity being performed is not within the scope of the desired movements and so no feedback will be given. In this specific case, the falling may be identified by the detection of a position other than normal, a sudden change of position, a sudden change of velocity and possibly a lack of movement altogether. This may cause the system to switch off, and not to give any feedback until, for example, it is detected that the user has mounted the horse again, and their movement pattern falls within the scope of the desired movements.

[0096] By collecting raw data related to position, acceleration and time, and comparing it to normal or OBP performance, the system is able to distinguish, recognize and acknowledge certain events in the user's movement pattern that are outside the scope of a specific activity (i.e. one for which feedback is required/desired). The main use of this feature is to distinguish between situations in which feedback is desired, and situations in which feedback is not desired, thus optimizing the performance of the system. Another advantage provided by this is the detection and labelling of activities that can be used to improve the OBP for this and other activities and the system in general.

[0097] The loop shown in FIG. 3C relates to the identification of the horse's gait. The system may employ an algorithm which can distinguish between different gaits such as walking, trotting, cantering, tlt, and flying pace. This may be done by reading the movement pattern of the sequence of footfalls, time delay between each hoof stance/print, and the speed moving forward. The z-direction movement associated with lateral, diagonal and leaping gaits is shown in FIG. 4.

[0098] Very few horses have pure gaits, i.e. their movements are individual in the same way that each person's movement pattern is individual. So, the system is advantageously able to gather data to establish each individual horse's individual movement pattern in each gait and adjust the feedback settings accordingly. Each time the horse places a hoof in the ground this will instigate a movement through the horse's body that will be transmitted to the rider of the horse, who is wearing the system of the invention. The movement through the horse is correlated to the swing of the horses back and the horse's movement pattern in that gait/height of the stride in the gait. The resulting pattern in the data will be connected to a motion in the z-direction (i.e. height off the ground) and speed forward.

[0099] Model: identify the horse's footfall and speed, over a certain time period/duration which will give rise to a specific pattern of z-direction movement of the body part in question of a user.

[0100] Horses move forward in what is defined as their gaits. There are five different gates; walk, tlt (also called running walk), trot, canter and the flying pace, where walk, trot and canter usually are defined as the horse's natural gaits. The gaits are differentiated by the pattern of the horse's hoofs hitting the ground, i.e. which leg(s) hit the ground and in what order. The walk, tlt and flying pace are all lateral gaits where the horse moves the legs on the same side of the body, i.e. left hind, left front, right hind, right front. The number of hoofs on the ground will vary with the speed in the lateral gaits.

[0101] In the walk the horse has usually 3 hoofs on the ground in each stride, in the tlt the horse has 1 to 3 hoofs on the ground and in the flying pace 0 (the suspended part) to 2 hoofs on the ground. Each time the horse puts a hoof on the ground it will result in an indication that can be recognized in the z-axis.

[0102] Each gait produces a very specific pattern of movement. In the lateral gaits the horse's back does not swing very much in the z-axis with each stride and the pattern of the lateral gait on the z-axis is usually level with four indications per specific time period. The main difference between lateral gaits is the speed i.e. how fast the rider and horse moves forward. Walking speed is around 6.5 km h.sup.1, tlt up to 32 km h.sup.1, and the flying pace up to 48 km h.sup.1.

[0103] The lateral gaits are four beat gaits where the pace has a period of suspension.

[0104] The trot is a diagonal gait in which the horse moves its left hind leg and right front leg simultaneously followed by a period of suspension and then simultaneous movement of the right hind leg and the left front leg. This two-beat rhythm produce a recognizable two beat pattern that is distinguishable from the lateral gaits.

[0105] In the diagonal movement the horse's back swings a lot, a motion that often is hard for the rider to absorb. The average speed is around 13 km h.sup.1.

[0106] The canter is a three beat leaping gate with an average speed of 16 to 27 km h.sup.1.

[0107] It is easier for the rider to absorb the movements from the horse in the lateral gaits (the walk, tlt and pace) but in trot, and canter it is more difficult to absorb the horse's motions because the back swings more in the z-axis i.e. the tolerance of deviation from the optimal position needs to be adjusted accordingly and by doing this the system is improved and optimized.

[0108] The problem with the model is that in reality, horses often do not have clear gaits. A lateral gate is supposed to have an identical time between each footfall of the horse, but in reality this can vary. Similarly, the trot is supposed to have the same time in between the two occasions when the opposite legs hit the ground, and the two diagonal pairs of hoofs are supposed to hit the ground at the same time. In reality, the pairs may not hit the ground simultaneously. There may also be other variations. Each horse has its own personal movement pattern.

[0109] The present invention is such that by collecting data about the different gaits, the deviations from the clear gaits can be identified from the collected data from each horse movement pattern. By operating the loop as shown in FIG. 3C, the learning will label and identify each horse's unclear gaits more and more accurately with each use. The collective identified patterns of deviation can be classified and labelled and used to optimize the system for all users. In a similar manner this concept can be applied to other activities that include specific parameters that may have a range of varieties to be defined.

[0110] While the invention has been described in conjunction with the exemplary embodiments described above, many equivalent modifications and variations will be apparent to those skilled in the art when given this disclosure. Accordingly, the exemplary embodiments of the invention set forth above are considered to be illustrative and not limiting. Various changes to the described embodiments may be made without departing from the spirit and scope of the invention.

[0111] All references referred to above are hereby incorporated by reference.