Wearable posture monitoring system

Abstract

The object of this invention is a wearable posture monitoring system and a method for monitoring the posture of a user, the system comprising: a wearable device comprising a wearable module; a sensor unit (1) comprising sensors mounted on the wearable module to monitor biomechanic parameters of the lumbar region of a user and generate biomechanical data; a processing device (2) comprising a machine learning model; a feedback device (3) generating feedback data providing feedback stimulus to a user. The machine learning model generates postural data based on obtained biomechanical data; and the processing device (2) instructs the feedback device (3) to generate feedback data based on the postural data and to provide a feedback stimulus to the user based generated feedback data. The proposed invention aims to promote corrective actions to improve the user's posture and provides a long-term historical analysis of the user's posture in a tailored adaptive manner.

Description

[0001] DESCRIPTION

[0002] WEARABLE POSTURE MONITORING SYSTEM

[0003] FIELD OF THE INVENTION

[0004] The present invention relates to a system and method for detecting poor posture and preventing musculoskeletal injuries.

[0005] PRIOR ART

[0006] Healthcare professionals are subjected to physically demanding and fast-paced work environments, which often result in excess strain in the body due to improper posture over prolonged periods of time, leading to work-related musculoskeletal disorders.

[0007] In particular, lumbar musculoskeletal injuries are prevalent among healthcare professionals, due to the demanding nature of their roles, for which a successful recovery requires prolonged resting periods and reduced physical efforts. The high rate of workplace injuries is a serious problem for healthcare organizations, involving high efforts to compensate for the absence of injured workers in recovery.

[0008] The traditional interventions to mitigate lumbar musculoskeletal injuries include physical therapy, ergonomics equipment, and recommendations. However, such approaches do not give continuous responses or update the influence of preventive measures or the recovery actions taken after getting injured. These methods are generally feedback-based, applied once a problem is identified, and do not include provisions for ongoing assessment and changes in the user's condition over time.

[0009] Other solutions are wearable technology in the form of devices that are meant to track and assess human biomechanics, especially in the area of posture and motion. Typically, these devices rely on a set of sensors to methodically record and analyze information relevant to the user's position and movement. However, these devices often use static threshold systems in which certain values are assigned to alert of poor posture or dangerous movements and they also do not consider the aspects such as body mechanics and postural habits of the people.

[0010] The proposed invention aims to address the aforementioned limitations by providing immediate feedback to the user, thereby promoting corrective actions to improve posture. In addition to real-time feedback, it offers a long-term historical analysis of the user's posture, delivering insights in a tailored and adaptive manner. This dual approach not only helps users correct their posture at the moment but also supports sustained improvements over time by adapting to the user's specific needs and changes in their condition.

[0011] SUMMARY OF THE INVENTION

[0012] The object of this invention consists of a wearable posture monitoring system comprising:

[0013] - a wearable device comprising a wearable module adapted to be fit on around the torso of a user; a sensor unit (1) comprised of a plurality of sensors mounted on the wearable module, being said plurality of sensors configured to monitor biomechanic parameters of the lumbar region of the user and to obtain biomechanical data;

[0014] - a processing device (2) comprising a machine learning model trained with biomechanical data;

[0015] - a feedback device (3) configured to generate feedback data and to provide a feedback stimulus to the user based on said feedback data; wherein the wearable device, processing device (2), and feedback device (3) are operatively connected, so that the machine learning model of the processing device (2) is configured to generate postural data based on the biomechanical data obtained from the sensor unit (1). The processing device (2) is further configured to instruct the feedback device (3) to generate feedback data based on the postural data and to provide a feedback stimulus to the user based on said feedback data. In an advantageous aspect of the present invention, the wearable posture monitoring system targets the prevention of pain in the lumbar region, which is one of the most common occupational hazards and musculoskeletal injuries of healthcare professionals, as the sensor unit (1) monitors biomechanical parameters from the lumbar region to obtain biomechanical data according to a user's physical orientation and motion, wherein the biomechanical parameters comprise orientation, velocity and magnetic fields; and the feedback device (3) provides an immediate feedback stimulus according to the posture of the user.

[0016] The feedback stimulus occurs upon the detection of suboptimal posture based on the postural data calculated by the machine learning model, alerting the user immediately and thus contributing to reinforce the adoption of optimal postural habits, which is particularly relevant when the user is subjected to high-stress and demanding circumstances, such as healthcare environments.

[0017] In an advantageous aspect of the present invention, the machine learning model trained with biomechanical data is able to generate postural data using a machine learning algorithm to process, in real-time, the biomechanical data captured by the sensors, which allows an adaptive understanding of the user's posture by continually refining the processed postural data. The continuous adaptive processing performed by the machine learning model stands as a major improvement compared to other solutions relying on rudimentary and static criteria.

[0018] In a preferred embodiment of the present invention, the wearable posture monitoring system further comprises a communication module; and the feedback device (3) comprises:

[0019] - a vibration unit (31), installed in the wearable device and configured to provide a tactile feedback stimulus to the user; and

[0020] - a user interface platform unit (32) adapted to provide a visual feedback stimulus to the user, through the communication module, by means of a mobile device application configured to communicate with said user interface platform unit (32) by means of a wide area network, local area network or personal area network.

[0021] In an advantageous aspect of the present invention, the user is immediately alerted by a tactile feedback stimulus if a suboptimal posture is detected, based on the postural data calculated by the machine learning model, which motivates the user to adopt a better posture in response to said tactile feedback stimulus. The tactile feedback stimulus is preferably in the form of vibration produced by the vibration unit (31).

[0022] In addition, the user interface platform unit (32) may provide a visual feedback stimulus, such as notifications displayed on a mobile device application, to motivate the user to adopt a better posture during the use of the wearable device.

[0023] The feedback device (3) may also generate feedback data to be consulted by the user over time through the mobile device application, to increase the awareness of the user about the postural habits adopted during the use of the wearable device, which motivates the user to adjust the posture to prevent musculoskeletal strain, pain and injury and also to improve the postural habits of the user over time.

[0024] The mobile device application may also provide gamification elements, including a leaderboard, to engage users into competition and peer-based accountability into what might otherwise be a monotonous routine.

[0025] DESCRIPTION OF THE FIGURES

[0026] Figure 1 - schematic representation of an embodiment of the wearable posture monitoring system, wherein the sensor unit (1) captures biomechanical data related to orientation, velocity and magnetic fields; a machine learning model of the processing device (2) then processes the captured biomechanical data and instructs feedback device (3) to generate feedback data based on the postural data and to provide a feedback stimulus to the user based on said feedback data. Figure 2 - schematic representation of an embodiment of the wearable posture monitoring system, wherein the vibration unit (31) of the feedback device (3) provides a tactile stimulus to the user in the form of vibration according to postural data calculated by the machine learning model within the processing device (2); and the user interface platform unit (32) of the feedback device (3) provides a visual feedback stimulus to the user, such as notifications displayed on a mobile device application.

[0027] DETAILED DESCRIPTION

[0028] The more general and advantageous configurations of the present invention are described in the Summary of the Invention. Such configurations are detailed below in accordance with other advantageous and / or preferred embodiments of implementation of the present invention.

[0029] In a preferred embodiment of the present invention, the postural data comprises at least one risk parameter so that the feedback device (3) is configured to generate feedback data based on the at least one risk parameter. The postural data generated by the machine learning model is then influenced by defined risk parameters to better adjust the thresholds for optimal and suboptimal postures of the user. Preferably, the postural data comprises a risk parameter for musculoskeletal injury.

[0030] In another embodiment of the present invention, the processing device (2) comprises a data storage means configured to store biomechanical data obtained by the plurality of sensors and processed postural data, generated by the machine learning model. This allows the system to store biomechanical data and processed postural data over long periods of time, wherein said stored biomechanical data may continually improve the calculations performed by the machine learning model. In a preferred embodiment of the present invention, the machine learning model is configured to calibrate the plurality of sensors based on biomechanical data, so that the monitoring action of the sensors is in optimal conditions and adjusted to the user.

[0031] In another embodiment of the present invention, the visual feedback stimulus comprises information regarding stretching or exercise routines based on the postural data, so that the user may be informed of targeted exercises and stretching routines to strengthen vulnerable areas and mitigate the risk of future injuries. This emphasizes the predictive aspect in addition to the real-time reactive aspect of the wearable posture monitoring system, wherein the user is alerted immediately upon the identification of a poor posture but is also informed of corrective measures that will take long-term effects to ensure proper posture and mitigate risk of injury.

[0032] In a preferred embodiment of the present invention, the sensor unit (1) comprises one or more of the selected group of sensors: accelerometer, gyroscope, magnetometer; wherein different biomechanical parameters, such as orientation, velocity or magnetic fields can be monitored. In addition, the communication module is configured to communicate with the sensor unit (1) by wireless communication, such as Wi-fi and Bluetooth, which allows the sensors to be activated and allows data to be transmitted remotely.

[0033] In another embodiment of the present invention, the wearable module comprises a power supply, preferably a recharging battery, a power supply light indicator signal and a charging port. In addition, the mobile device application may include energy-efficient features and may provide notifications to the user when the battery is low and requires charging.

[0034] In a preferred embodiment of the present invention, the wearable device comprises a belt featuring an adjustable fit, lightweight materials, and hypoallergenic components, which prioritize wearability and comfort to the user for extended periods of time. It is also an object of the present invention a method for monitoring the posture of a user performed by the wearable posture monitoring system, comprising the following steps:

[0035] - Sensor calibration, wherein a machine learning algorithm calibrates the sensors to ensure optimal biomechanical data capture conditions;

[0036] - Biomechanical data capture, wherein the sensors capture data related to orientation, velocity and magnetic fields;

[0037] - Real-time biomechanical data processing, wherein a machine learning algorithm interprets and categorizes several postural metrics; and

[0038] - Reactive Feedback, wherein the vibration unit (31) is activated to generate a tactile alert to the user if a postural deviation or potential risk factor is identified, to prompt the user to correct their posture and to prevent injury.

[0039] In addition, the method may also perform the steps of:

[0040] - Predictive analysis, wherein a machine learning algorithm analyzes historical captured biomechanical data or processed postural data to identify patterns and predict potential risks for musculoskeletal injury of the user;

[0041] - Data transmission to mobile application, wherein the captured biomechanical data and processed postural data is transmitted to a dedicated mobile application via Wi-fi or Bluetooth communication;

[0042] - In response to the detection of a high-risk pattern, alert the user via mobile application and suggest corrective measures; and

[0043] - Suggest personalized stretching or exercise routines via the mobile application, wherein the suggestions are based on the captured biomechanical data and processed postural data.

[0044] The preferred embodiments described above can, of course, be combined in various configurations, being the present invention not limited to the embodiments previously described.

Claims

CLAIMS1. A wearable posture monitoring system comprising:- a wearable device comprising a wearable module adapted to be fit on around the torso of a user; a sensor unit (1) comprised of a plurality of sensors mounted on the wearable module, being said plurality of sensors configured to monitor biomechanic parameters of the lumbar region of the user and to generate biomechanical data;- a processing device (2) comprising a machine learning model trained with biomechanical data;- a feedback device (3) configured to generate feedback data and to provide a feedback stimulus to the user based on said feedback data; wherein the wearable device, the processing device (2) and the feedback device (3) are operatively connected so that the machine learning model of the processing device (2) is configured to generate postural data based on the biomechanical data obtained by the sensor unit (1); and the processing device (2) is further configured to instruct the feedback device (3) to generate feedback data based on the postural data and to provide a feedback stimulus to the user based on said feedback data.

2. System according to claim 1 further comprising a communication module and wherein the feedback device (3) comprises:- a vibration unit (31), installed in the wearable device and configured to provide a tactile feedback stimulus to the user; and- a user interface platform unit (32) adapted to provide a visual feedback stimulus to the user, through the communication module, by means of a mobile device application configured to communicate with said user interface platform unit (32) by means of a wide area network, local area network or personal area network.

3. System according to any one of claims 1- 2, wherein the postural data comprises at least one risk parameter so that the feedback device (3) is configured to generate feedback data based on at least one risk parameter.

4. System according to claim 3, wherein the postural data comprises a risk parameter for musculoskeletal injury.

5. System according to any one of claims 1 - 4, the processing device (2) comprises a data storage means configured to store biomechanical data obtained by the plurality of sensors and processed postural data.

6. System according to anyone of claims 1 -5, wherein the machine learning model is configured to calibrate the plurality of sensors based on biomechanical data.

7. System according to any one of claims 2- 6, wherein the visual feedback stimulus comprises information regarding stretching or exercise routines based on the postural data.

8. System according to any one of claims 1 - 7, comprising one or more of the selected group of sensors: accelerometer, gyroscope, magnetometer.

9. System accordingto anyone of claims 1-8, wherein the communication module is configured to communicate with the sensor unit (1) by wireless communication.

10. System according to any one of claims 1 - 9, wherein the wearable device comprises a power supply, a power supply light indicator signal, and a charging port, wherein the power supply further comprises a recharging battery.

11. System according to any one of claims 1 - 10, wherein the wearable module comprises a belt.

12. A method for monitoring the posture of a user performed by the wearable posture monitoring system of any one of claims 1 - 11, comprising the following steps:- Sensor calibration, wherein a machine learning algorithm calibrates the sensors to ensure optimal biomechanical data capture conditions;- Biomechanical data capture, wherein the sensors capture data related to orientation, velocity and magnetic fields;- Real-time biomechanical data processing, wherein a machine learning algorithm interprets and categorizes several postural metrics; and- Reactive Feedback, wherein the vibration unit (31) is activated to generate a tactile alert to the user if a postural deviation or potential risk factor is identified, to prompt the user to correct their posture and to prevent injury.

13. A method for monitoring the posture of a user according to claim 12 comprising the following steps:- Predictive analysis, wherein a machine learning algorithm analyzes historical captured biomechanical data or processed postural data to identify patterns and predict potential risks for musculoskeletal injury of the user;- Data transmission to a mobile application, wherein the captured biomechanical data and processed postural data are transmitted to a dedicated mobile application via Wi-fi communication; and- In response to the detection of a high-risk pattern, alert the user via mobile application and suggest corrective measures.

14. A method for monitoring the posture of a user according to any one of claims 12- 13, comprising the following step:- Suggest personalized stretching or exercise routines via a mobile application, wherein the suggestions are based on the captured biomechanical data and processed postural data.

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