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Deep Camera-Based Movement Analysis for Remote Rehabilitation and Physical Therapy

To develop a mobile application that leverages advanced 3D pose estimation technology for tracking and analyzing a person’s movement outside traditional laboratory settings. This app aims to complement the clinician’s work by enabling remote monitoring and interaction between patients and healthcare providers, thus facilitating data-driven physiotherapy and rehabilitation sessions.

The benefits of such an approach include:

  • Adaptive, personalized therapy to each patient’s progress and needs
  • Progress tracking highlighting achievements and areas needing attention
  • Assisting in correct execution by providing immediate feedback



The need for innovative tools that offer quantitative insights into patients’ movements has become increasingly apparent, particularly for remote or home-based physiotherapy and rehabilitation. Traditional methods often rely on in-person assessments that may not fully capture the nuances of a patient’s progress or challenges.

An app that provides accurate, quantitative movement analysis can significantly enhance the clinician’s ability to tailor treatments, monitor progress remotely, and ensure patients perform exercises correctly while reducing the need for frequent in-person visits.

The current app demo utilizes a single smartphone or tablet to capture a person’s 3D movement using the device’s depth camera capabilities. To ensure high accuracy and reliability, the app employs a machine learning model to refine and improve pose estimation based on data collected from a wide range of users. The current implementation primarily targets the lower extremities, focusing on walking. Efforts are underway to broaden the model’s scope to encompass a broader range of movements.

Crossdisciplinary collaboration
The project partners are Innovations Office Region Stockholm and Danderyd University Hospital.

Watch the recorded presentation at the Digitalize in Stockholm 2023 event:



Picture of Lanie Gutierrez Farewik

Elena Gutierrez Farewik

Professor, Department of Engineering Mechanics at KTH, Member of the Strategic Research Committee, Chair Working group Rich and Healthy Life, PI of project Deep Camera-Based Movement Analysis for Remote Rehabilitation and Physical Therapy, PI of project Real-time exoskeleton control for human-in-the-loop optimization, Digital Futures Faculty

+46 8 790 77 19