WO2024080957A1 - A system for physiotherapy monitoring and a related method thereof - Google Patents

A system for physiotherapy monitoring and a related method thereof Download PDF

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Publication number
WO2024080957A1
WO2024080957A1 PCT/TR2023/051120 TR2023051120W WO2024080957A1 WO 2024080957 A1 WO2024080957 A1 WO 2024080957A1 TR 2023051120 W TR2023051120 W TR 2023051120W WO 2024080957 A1 WO2024080957 A1 WO 2024080957A1
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WIPO (PCT)
Prior art keywords
sensor
limb
data
processing unit
user
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PCT/TR2023/051120
Other languages
French (fr)
Inventor
Guzin TURKMEN
Gokhan SENGUL
Original Assignee
Atilim Universitesi
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Publication date
Priority claimed from TR2022/015540 external-priority patent/TR2022015540A1/en
Application filed by Atilim Universitesi filed Critical Atilim Universitesi
Publication of WO2024080957A1 publication Critical patent/WO2024080957A1/en

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A61B5/1114—Tracking parts of the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades

Definitions

  • the present invention relates to a system and method for controlling a user’s physiotherapy movements and transmitting them for expert control.
  • Physiotherapy is often used in the treatment of many disorders in order to relieve pain, enhance functionality and/or mobility (ability to move), and improve or regain daily living activities.
  • patients perform various physical movements that are specifically prepared for the related disorder, in a predetermined manner, number and time.
  • Physiotherapy sessions are generally carried out in company with a physiotherapist and besides, after a certain period of time, patients continue the physical movements recommended by the physiotherapist in their own environment.
  • parameters such as the degree of the stretching motion, the number of repetitions, and the duration of holding the stretched position are predetermined.
  • the patients perform these exercises in their own environment it is not possible to verify the accuracy of these parameters. Therefore, it may not be possible to detect whether these movements are done incorrectly or problems resulting from incorrect movements can not be determined until the patient consults with the physiotherapist again.
  • the system disclosed in the United States patent document with publication no. US2020093418 Al relates to a new system for monitoring patients in need of physiotherapy, both in the clinic and at home, by using three axes accelerometers and three axes gyroscopes as motion sensors.
  • a machine learning procedure is implemented for ensuring a continuous assessment of the exercise program changes and program evaluation.
  • the progress of the patient’s flexion is automatically analyzed against patterns already existing in the database and depending on the detected improvements; it generates relevant notifications, alerts, and, finally, a better selection and scheduling of the exercises and automatic personalization of the patient schedule.
  • the invention disclosed in the United States patent document with publication no. US2012259652 Al relates to a system which allows remote monitoring of movements according to data received from various sensors in order to develop treatment plans, monitor progress and compliance of treatment, adjust and optimize treatment plans, and measure outcomes related to the treatment plans.
  • the main objective of the present invention is to increase precision in control of physiotherapy movements performed by a user.
  • Another objective of the present invention is to collect data without online requirement and to ensure the processing of this data.
  • Another objective of the present invention is to detect accuracy of movements on the basis of machine learning.
  • the present invention relates to a system for monitoring a user’s physiotherapy movements in order to meet the above-mentioned requirements and objectives.
  • the present invention comprises at least one four-axis sensor which is intended for providing data related to a user’s limb position, at least one processing unit which is configured to process the data provided from a sensor so as to detect the position of a sensor or the movement orientation of a limb, and a storage unit wherein the processed sensor data will be stored.
  • the said detection precision is increased by providing a six-axis type sensor in particular.
  • Figure l is a representative schematic image view of the inventive system.
  • the subject of the present invention relates to a system (1) and method for controlling a user’s (U) physiotherapy movements and transmitting them for expert control.
  • the inventive system (1) comprises at least one, preferably a plurality of sensors (S).
  • the sensors (S) are detection devices which are arranged specifically for location/position detection.
  • the said sensors (S) may comprise various connection elements so as to be connected to various areas on the user’s (U) body.
  • the said sensors (S) may be provided in such a way that they are connected to straps configured to be attached or fixed to the joints or various body limbs of the user.
  • a mobile user device (U) for example a smart watch- can be used in the function of the abovementioned sensor (S) structure so as to have the necessary sensors (S).
  • the basic requirement is to provide at least a four- axis, preferably six-axis sensor (S).
  • the highest precision is achieved with the six- axis sensor (S).
  • the sensor (S) provided with at least four-axis may comprise an accelerometer and a gyroscope with at least one axis, preferably a multi-axis accelerometer and a gyroscope.
  • the said system (1) also comprises a processing unit (PU) to process the data provided from sensors.
  • the processing unit (PU) is configured to detect the user’s (U) area where physiotherapy is applied for treatment and/or the position of another area connected to it, according to the sensor data.
  • the processing unit (PU) is configured to detect the movement orientation according to the data provided from the sensor (S) as well. Besides, calculations can be made directly from data received from motion and orientation sensors, in angle measurements. In addition, time window shifting methods (such as DWT) can be used in motion detection as well.
  • the processing unit (PU) is also configured to detect how long the sensors (S) remain at a certain point or in the range of a certain margin of error at least according to a certain point.
  • the processing unit (PU) can also count how many times the user (U) repeats the physiotherapy movement.
  • the processing unit (PU) is also configured to detect how many times the sensors (S) move at at least two certain points or in the range of a certain margin of error according to at least two certain points.
  • the said processing unit (PU) can also operate in integration with a memory unit. Predetermined movement patterns of muscles and/or limbs are included in the memory unit.
  • the processing unit (PU) is configured to detect the position and/or the orientation of the related movement by comparing the data received from the sensor (S) with the said patterns.
  • multiple sensors (S) are used and the processing unit (PU) is configured to process the positions of the said sensors (S) relative to one another so as to determine the success of the said physiotherapy movement. For example, considering the sensors (S) attached to the shoulder, sensors mounted on elbow and wrist and the positions of these sensors (S) relative to one another will enable to determine the movement more accurately, in comparison to a sensor (S) to be attached only to the wrist.
  • the processing unit is also configured to calculate at what angle the limb being monitored is bent from the joint points, according to the position of the sensor attached to a plurality of points.
  • the said processing unit (PU) may be a device which is provided in integration with the sensor (S) directly.
  • the processing unit (PU) processes the sensor (S) data provided by an internal communication unit and obtains the result.
  • the sensors (S) may be configured to communicate with the processing unit (PU) in a wired or wireless way via protocols such as Wi-Fi, GSM, Bluetooth, Ethernet.
  • the processing unit (PU) can be provided in integration with a wired or wireless communication unit so as to transmit the obtained data to an external device.
  • the said external device may be a server having at least one storage unit (SU) or a user device (UD) having the necessary hardware to transmit data to the said server, such as smartphone, tablet and computer.
  • the processing unit (PU) is provided in integration with a user device (UD) such as a smart mobile phone, tablet and computer.
  • a user device such as a smart mobile phone, tablet and computer.
  • the data read from the sensors (S) is transmitted to the user device (UD) in a wired or wireless way.
  • the user device (KU) data can be viewed or the said data can be transferred to the server as well.
  • the processing unit (PU) is provided on the sensor (S) or the user device (UD)
  • the processing unit (PU) is provided on the sensor (S) or the user device (UD)
  • the processing unit (PU) is provided on the sensor (S) or the user device (UD)
  • the obtained results are transmitted to the server in a wired or wireless way.
  • the processing unit (PU) can be provided on the server.
  • the sensor (S) or sensors (S) which control the movements of the user (U) transfer the raw data they obtain to the server by means of the wired or wireless communication units integrated into them or to a user device (UD) having the necessary hardware to transmit the data to the said server, such as smart mobile phone, tablet and computer.
  • UD user device
  • the said data can be written to the space allocated for the user (U) in a storage unit (SU) included in the server and the said space can be accessed over the host device (D) which is controlled by the user (U) and/or a physician or physiotherapist, such as a smart mobile phone, tablet and computer.
  • the said data can also be provided in the form of reports which can be accessed by a user or physician.
  • access to the related memory area can be provided via username, password or authentication systems known in the state of the art.
  • access to the related memory area can be provided via username, password or authentication systems known in the state of the art.
  • a physician or physiotherapist checks the movements of the user (U), s/he can enter inputs that will be transmitted to the user device (UD) on the same server or over this server.
  • These inputs may be based on whether the movement is correct or incorrect and they can be provided so as to create a request for a video or face-to-face meeting with the patient.
  • the communication between the said sensor (S), the user device (UD), the storage unit (SU), the processing unit (PU) and the host device (D) may be an application, preferably an application executed on the user device (UD), particularly a mobile application.
  • the said processing unit (PU) is also configured to execute a model created by means of methods intended for machine learning.
  • the machine learning model can be trained by means of controlled or uncontrolled training methods.
  • measurements such as the angles of the hand and arm relative to each other and to the body, the angles of the foot and knee to each other and to the body, the completion time of the movement, the acceleration occurring while performing the movement, performing the movement by touching a fixed ground or not, the number of repetitions and the time between repetitions can be used as an attribute.
  • Parameters for the movements of users who have specific disorders are marked as correct or incorrect or partially correct or incorrect, preferably by a physician or physiotherapist in order to create training and test data.
  • the model is trained upon the said data is separated as training and test data in an appropriate ratio. Besides, new data received from users (U) can be used as data to improve the model by being marked appropriately or in an uncontrolled way. By means of this model, the need for physician or physiotherapist control can be eliminated entirely.
  • the user (U) connects the sensor (S) or the sensors (S) to the limb or the area related to the limb where physiotherapy application will be performed appropriately at first.
  • the senor (S) or the sensors (S) are calibrated before commencement of action.
  • the user (U) can remain stable in a certain posture or provide calibration by repeating the desired movements.
  • the predetermined instruction movements can be displayed preferably on the user device (UD).
  • the user (U) can follow these instructions.
  • the sensor (S) or the sensors (S) start to create data.
  • the said data is transmitted to a processing unit (PU).
  • the data is evaluated according to predetermined intervals or models and then a result is obtained or a result is obtained by feeding the said data to a machine learningbased model as input.
  • the said results are processed in a memory area and here, the related data area can be accessed by the user (U) and a physician.

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Abstract

The present invention relates to a system for monitoring a user's (U) physiotherapy movements which comprises at least one four-axis sensor (S) intended for providing data related to a user's (U) limb position, at least one processing unit (PU) configured to process the data provided from a sensor (S) so as to detect the position of a sensor or the movement orientation of a limb, and a storage unit (SU) wherein the processed sensor (S) data will be stored.

Description

A SYSTEM FOR PHYSIOTHERAPY MONITORING AND A RELATED METHOD THEREOF
Technical Field of the Invention
The present invention relates to a system and method for controlling a user’s physiotherapy movements and transmitting them for expert control.
Background of the Invention
Physiotherapy is often used in the treatment of many disorders in order to relieve pain, enhance functionality and/or mobility (ability to move), and improve or regain daily living activities. In physiotherapy, patients perform various physical movements that are specifically prepared for the related disorder, in a predetermined manner, number and time. Physiotherapy sessions are generally carried out in company with a physiotherapist and besides, after a certain period of time, patients continue the physical movements recommended by the physiotherapist in their own environment.
If the related movements are not performed correctly as a whole during physiotherapy, the therapy becomes useless and may even harm the patient and make the healing process regress. In order to prevent potential problems, critical parameters such as opening angle are measured manually by a specialist in the clinical environment in current applications.
For example, in a stretching exercise, parameters such as the degree of the stretching motion, the number of repetitions, and the duration of holding the stretched position are predetermined. However, when the patients perform these exercises in their own environment, it is not possible to verify the accuracy of these parameters. Therefore, it may not be possible to detect whether these movements are done incorrectly or problems resulting from incorrect movements can not be determined until the patient consults with the physiotherapist again.
The system disclosed in the United States patent document with publication no. US2020093418 Al relates to a new system for monitoring patients in need of physiotherapy, both in the clinic and at home, by using three axes accelerometers and three axes gyroscopes as motion sensors. In the application, a machine learning procedure is implemented for ensuring a continuous assessment of the exercise program changes and program evaluation. The progress of the patient’s flexion is automatically analyzed against patterns already existing in the database and depending on the detected improvements; it generates relevant notifications, alerts, and, finally, a better selection and scheduling of the exercises and automatic personalization of the patient schedule.
The invention disclosed in the United States patent document with publication no. US2012259652 Al relates to a system which allows remote monitoring of movements according to data received from various sensors in order to develop treatment plans, monitor progress and compliance of treatment, adjust and optimize treatment plans, and measure outcomes related to the treatment plans.
In the system disclosed in the International patent document with publication no. W02011063079 A2, multiple sensors are used to track body part motion. The tracked motion may then be compared to prescribed motion and also be stored for ascertaining compliance with a prescribed therapy regimen.
In the International patent document with publication no. WO2021226445 Al, physiotherapy movements are converted into data by means of sensors placed on the patient’s body and here, these movements are visualized over an avatar. A physiotherapist can control accuracy of movements over this avatar. In the above-mentioned systems, it is of great importance to turn the movement read from the sensor into data completely and correctly. In the event that the movement cannot be transferred to the system correctly, even the one performed correctly may be marked as incorrect.
Another important drawback is that the said systems need to transmit data, which is received from sensors, to a server due to the fact that they generally process it in a remote server. Accordingly, these systems lose most of their functions when they are not online.
Consequently, all above-mentioned systems problems have made it necessary to make innovation in the related field.
Objects and Short Description of the Invention
The main objective of the present invention is to increase precision in control of physiotherapy movements performed by a user.
Another objective of the present invention is to collect data without online requirement and to ensure the processing of this data.
Another objective of the present invention is to detect accuracy of movements on the basis of machine learning.
The present invention relates to a system for monitoring a user’s physiotherapy movements in order to meet the above-mentioned requirements and objectives. Accordingly, the present invention comprises at least one four-axis sensor which is intended for providing data related to a user’s limb position, at least one processing unit which is configured to process the data provided from a sensor so as to detect the position of a sensor or the movement orientation of a limb, and a storage unit wherein the processed sensor data will be stored. The said detection precision is increased by providing a six-axis type sensor in particular.
Besides, user movements are evaluated by means of artificial intelligence in the said system. Accordingly, the need for a physician or physiotherapist opinion is reduced or completely eliminated.
Definitions of Figures Explaining the Invention
The figures and related descriptions used to further explain the device developed through the present invention are as follows.
Figure l is a representative schematic image view of the inventive system.
Definitions of Elements/Parts/Components Composing the Invention
The components and parts included in the figure so that the device developed through the present invention can be further explained are numbered and the equivalent of each number is given below:
1. System
D. Host device
S. Sensor
U. User
UD. User device
SU. Storage unit
PU. Processing unit
Detailed Description of the Invention The subject of the present invention relates to a system (1) and method for controlling a user’s (U) physiotherapy movements and transmitting them for expert control.
With reference to the Figure 1, the inventive system (1) comprises at least one, preferably a plurality of sensors (S). The sensors (S) are detection devices which are arranged specifically for location/position detection. The said sensors (S) may comprise various connection elements so as to be connected to various areas on the user’s (U) body. For example, the said sensors (S) may be provided in such a way that they are connected to straps configured to be attached or fixed to the joints or various body limbs of the user.
Alternatively, a mobile user device (U) -for example a smart watch- can be used in the function of the abovementioned sensor (S) structure so as to have the necessary sensors (S). Here, the basic requirement is to provide at least a four- axis, preferably six-axis sensor (S). The highest precision is achieved with the six- axis sensor (S). Here, the sensor (S) provided with at least four-axis may comprise an accelerometer and a gyroscope with at least one axis, preferably a multi-axis accelerometer and a gyroscope.
The said system (1) also comprises a processing unit (PU) to process the data provided from sensors. Here, the processing unit (PU) is configured to detect the user’s (U) area where physiotherapy is applied for treatment and/or the position of another area connected to it, according to the sensor data. Furthermore, in one preferred embodiment, the processing unit (PU) is configured to detect the movement orientation according to the data provided from the sensor (S) as well. Besides, calculations can be made directly from data received from motion and orientation sensors, in angle measurements. In addition, time window shifting methods (such as DWT) can be used in motion detection as well. Moreover, the processing unit (PU) is also configured to detect how long the sensors (S) remain at a certain point or in the range of a certain margin of error at least according to a certain point.
Additionally, the processing unit (PU) can also count how many times the user (U) repeats the physiotherapy movement. For this purpose, the processing unit (PU) is also configured to detect how many times the sensors (S) move at at least two certain points or in the range of a certain margin of error according to at least two certain points.
The said processing unit (PU) can also operate in integration with a memory unit. Predetermined movement patterns of muscles and/or limbs are included in the memory unit. The processing unit (PU) is configured to detect the position and/or the orientation of the related movement by comparing the data received from the sensor (S) with the said patterns.
In one preferred embodiment, multiple sensors (S) are used and the processing unit (PU) is configured to process the positions of the said sensors (S) relative to one another so as to determine the success of the said physiotherapy movement. For example, considering the sensors (S) attached to the shoulder, sensors mounted on elbow and wrist and the positions of these sensors (S) relative to one another will enable to determine the movement more accurately, in comparison to a sensor (S) to be attached only to the wrist.
In one preferred embodiment, the processing unit (PU) is also configured to calculate at what angle the limb being monitored is bent from the joint points, according to the position of the sensor attached to a plurality of points.
The said processing unit (PU) may be a device which is provided in integration with the sensor (S) directly. Here, the processing unit (PU) processes the sensor (S) data provided by an internal communication unit and obtains the result. Here, in the event that a plurality of sensors (S) are used, the sensors (S) may be configured to communicate with the processing unit (PU) in a wired or wireless way via protocols such as Wi-Fi, GSM, Bluetooth, Ethernet. Furthermore, the processing unit (PU) can be provided in integration with a wired or wireless communication unit so as to transmit the obtained data to an external device. The said external device may be a server having at least one storage unit (SU) or a user device (UD) having the necessary hardware to transmit data to the said server, such as smartphone, tablet and computer.
In another embodiment, the processing unit (PU) is provided in integration with a user device (UD) such as a smart mobile phone, tablet and computer. Here, the data read from the sensors (S) is transmitted to the user device (UD) in a wired or wireless way. The user device (KU) data can be viewed or the said data can be transferred to the server as well.
In these applications wherein the processing unit (PU) is provided on the sensor (S) or the user device (UD), there is no requirement for an online connection in order to obtain result; but if desired, the obtained results are transmitted to the server in a wired or wireless way.
Alternatively, the processing unit (PU) can be provided on the server. Here, the sensor (S) or sensors (S) which control the movements of the user (U) transfer the raw data they obtain to the server by means of the wired or wireless communication units integrated into them or to a user device (UD) having the necessary hardware to transmit the data to the said server, such as smart mobile phone, tablet and computer. Although this condition is advantageous for the requirement of transaction power necessary in the devices included on the user (U) part, the transmission requirement of the said raw data creates an obligation to remain online. The said data can be written to the space allocated for the user (U) in a storage unit (SU) included in the server and the said space can be accessed over the host device (D) which is controlled by the user (U) and/or a physician or physiotherapist, such as a smart mobile phone, tablet and computer. The said data can also be provided in the form of reports which can be accessed by a user or physician.
Here, access to the related memory area can be provided via username, password or authentication systems known in the state of the art. At this point, upon a physician or physiotherapist checks the movements of the user (U), s/he can enter inputs that will be transmitted to the user device (UD) on the same server or over this server.
These inputs may be based on whether the movement is correct or incorrect and they can be provided so as to create a request for a video or face-to-face meeting with the patient.
The communication between the said sensor (S), the user device (UD), the storage unit (SU), the processing unit (PU) and the host device (D) may be an application, preferably an application executed on the user device (UD), particularly a mobile application.
The said processing unit (PU) is also configured to execute a model created by means of methods intended for machine learning. The machine learning model can be trained by means of controlled or uncontrolled training methods. In the machine learning model, measurements such as the angles of the hand and arm relative to each other and to the body, the angles of the foot and knee to each other and to the body, the completion time of the movement, the acceleration occurring while performing the movement, performing the movement by touching a fixed ground or not, the number of repetitions and the time between repetitions can be used as an attribute. Parameters for the movements of users who have specific disorders (movement type, duration, angle and etc.) are marked as correct or incorrect or partially correct or incorrect, preferably by a physician or physiotherapist in order to create training and test data. The model is trained upon the said data is separated as training and test data in an appropriate ratio. Besides, new data received from users (U) can be used as data to improve the model by being marked appropriately or in an uncontrolled way. By means of this model, the need for physician or physiotherapist control can be eliminated entirely.
In the computer application method intended for the inventive system, the user (U) connects the sensor (S) or the sensors (S) to the limb or the area related to the limb where physiotherapy application will be performed appropriately at first.
Optionally, the sensor (S) or the sensors (S) are calibrated before commencement of action. For the calibration process, the user (U) can remain stable in a certain posture or provide calibration by repeating the desired movements.
After the calibration transaction, the predetermined instruction movements can be displayed preferably on the user device (UD). The user (U) can follow these instructions.
As a result of the user (U) movement, the sensor (S) or the sensors (S) start to create data. The said data is transmitted to a processing unit (PU). Here, the data is evaluated according to predetermined intervals or models and then a result is obtained or a result is obtained by feeding the said data to a machine learningbased model as input.
The said results are processed in a memory area and here, the related data area can be accessed by the user (U) and a physician.

Claims

CLAIMS A system (1) for monitoring a user’s (U) physiotherapy movements; characterized in that it comprises a six-axis sensor (S) which is intended for providing data related to a user’s (U) limb position; at least one processing unit (PU) which is configured to process the data provided from a sensor (S) so as to detect the position of a sensor or the movement orientation of a limb; a storage unit (SU) wherein the processed sensor (S) data will be stored. A system (1) according to Claim 1; characterized in that the said sensor (S) comprises an accelerometer and a gyroscope with at least one axis. A system (1) according to Claim 2; characterized in that the said accelerometer and gyroscope are multi-axis. A system (1) according to any of the preceding claims; characterized in that it comprises a plurality of sensors (S). A system (1) according to Claim 1; characterized in that the said processing unit (PU) is configured to detect the bending angle of a limb. A system (1) according to Claim 1; characterized in that the said processing unit (PU) is configured to detect how long the sensors (S) remain at a certain point or in the range of a certain margin of error at least according to a certain point. A system (1) according to Claim 1; characterized in that the said processing unit (PU) is configured to provide a transaction of counting movements according to the movements of the sensors (S) between these points at at least two certain points or in the range of a certain margin of error according to at least two certain points.
8. A system (1) according to Claim 4; characterized in that the said processing unit (PU) is configured to calculate at what angle the limb being monitored is bent from the joint points, according to the position of the sensor (S) attached to a plurality of points.
9. A system (1) according to any of the preceding claims; characterized in that the said processing unit (PU) is configured to compare the sensor (S) data according to predetermined coordinate models.
10. A system (1) according to any of Claim 1-8; characterized in that the said processing unit (PU) is configured to compare the sensor (S) data according to predetermined movement or limb or muscle patterns.
11. A system (1) according to any of Claim 1-8; characterized in that the said processing unit (PU) is configured to process the sensor (S) data by using a machine learning-based model.
12. A system (1) according to Claim 1; characterized in that it comprises at least one user device (UD).
13. A system (1) according to Claim 12; characterized in that the said user device (UD) is a smart watch, smart mobile phone, tablet or computer.
14. A system (1) according to Claim 12 or 13; characterized in that it comprises a communication unit for the communication of the said user device (UD) and the storage unit (SU).
15. A system (1) according to Claim 1; characterized in that the said processing unit (PU) is provided on the user device (UD).
16. A system (1) according to Claim 1; characterized in that the said processing unit (PU) is provided on a server together with the storage unit (SU).
17. A system (1) according to Claim 1; characterized in that it comprises at least one host device (D).
18. A system (1) according to Claim 17; characterized in that the said host device (D) is a smart watch, smart mobile phone, tablet or computer.
19. A system (1) according to Claim 17 or 18; characterized in that it comprises a communication unit for the communication of the said host device (D) and the storage unit (SU).
20. A system (1) according to Claim 1; characterized in that the said sensor (S) and the processing unit (PU) are provided integratedly.
21. A system (1) according to Claim 1 or 20; characterized in that the said sensor (S) is provided on a smart watch.
22. A computer-implemented method for monitoring a user’s (U) physiotherapy movements; characterized in that it comprises steps of calibrating at least one sensor (S) which is configured to provide data about the position of a user (U) limb; detecting the position of a sensor (S) or the movement orientation of a limb according to the data provided from the sensor (S); detecting whether the position of a sensor (S) or the movement orientation of a limb is correct or not according to the obtained data.
23. A method according to Claim 22; characterized in that the bending angle of a limb is detected according to the obtained data.
24. A method according to Claim 22; characterized in that it is detected how long the said sensor (S) remains at a certain point or in the range of a certain margin of error at least according to a certain point.
25. A method according to Claim 22; characterized in that a transaction of counting movements is provided according to the movements of the sensor (S) between at least two certain points or in the range of a certain margin of error according to at least two certain points.
26. A method according to Claim 22; characterized in that it is calculated at what angle the limb being monitored is bent from the joint points, according to the position of the sensor (S) attached to a plurality of points.
27. A method according to Claim 22; characterized in that the data received from the sensor (S) for controlling the position of a sensor (S) or the movement orientation of a limb is compared with predetermined coordinate patterns.
28. A method according to Claim 22; characterized in that the sensor (S) position and orientation are compared with predetermined movement or limb or muscle patterns to verify the orientation of limb movement.
29. A method according to Claim 22; characterized in that the sensor (S) data are fed to a machine learning-based model for controlling the position of a sensor (S) or the movement orientation of a limb.
PCT/TR2023/051120 2022-10-12 2023-10-12 A system for physiotherapy monitoring and a related method thereof WO2024080957A1 (en)

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TR2022015540 2022-10-12
TR2022/015540 TR2022015540A1 (en) 2022-10-12 A SYSTEM AND RELATED METHOD FOR PHYSIOTHERAPY MONITORING

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