Digital Physical Therapy


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Physical therapy is applied at every stage of the rehabilitation process, from diagnosis to restoration and recovery. Physical therapy can be used independently or in conjunction with other treatments. Before the coronavirus outbreak, many people felt that physical therapy was essentially a manual treatment. Many physiotherapy patients have chosen remote physiotherapy over in-person treatment because they are encouraged to stay at home and skip non-essential appointments. Even in the case of serious conditions, remote physical therapy is a viable outpatient treatment option. However with the help of new technology, it is possible to fix this problem.

So we are in the process of developing a camera based solution to detect the patients’ movements. The motion video must be collected from the patient using the built-in camera in the tablets or devices. With the model evaluation and results, the therapist should be able to guide the patient. Both the physical therapist and the patient should be able to compare the starting point to the current point, as well as the improvement over time.

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The primary goal of the built-in camera was to assess the patients’ particular movements. Then the collected data will be displayed in the physiotherapist’s device.

The MediaPipe Pose is a ML solution, used for high-fidelity body pose tracking, inferring 33 3D landmarks and background segmentation masks on the whole body from RGB video frames.

SenzMate pose detection solution helps to achieve real-time performance on most modern mobile phones, desktops, in python and on the web.

Digital physical therapy helps to improve adherence and improves outcomes, improves access and lowers the socioeconomic barriers to care, provides the best preventive care for the patients.

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We developed even more enhancements by consulting with medical specialists and identifying additional indicators and patterns to evaluate patients’ status, as well as improving methods to monitor the parameters more accurately.

Further improvements were made by making the model work in portable devices. The framework was converted to a mobile friendly version. The model was optimized for light weight deployment.

Steps Forward (Future plans):

A mobile application to display historical reports for patients’ with different templates for their conditions, performance insights and graphical visualizations.

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