mlsanityData to 14 Oct 2026

A HRNet-based Rehabilitation Monitoring System

arXiv 2306.10756 ↗First posted 19 Jun 2023cs.CV cs.AIcited by 0

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Abstract (arXiv)

The rehabilitation treatment helps to heal minor sports and occupational injuries. In a traditional rehabilitation process, a therapist will assign certain actions to a patient to perform in between hospital visits, and it will rely on the patient to remember actions correctly and the schedule to perform them. Unfortunately, many patients forget to perform actions or fail to recall actions in detail. As a consequence, the rehabilitation treatment is hampered or, in the worst case, the patient may suffer from additional injury caused by performing incorrect actions. To resolve these issues, we propose a HRNet-based rehabilitation monitoring system, which can remind a patient when to perform the actions and display the actions for the patient to follow via the patient's smartphone. In addition, it helps the therapist to monitor the progress of the rehabilitation for the patient. Our system consists of an iOS app and several components at the server side. The app is in charge of displaying and collecting action videos. The server computes the similarity score between the therapist's actions and the patient's in the videos to keep track of the number of repetitions of each action. Theses stats will be shown to both of the patient and therapist. The extensive experiments show that the F1-Score of the similarity calculation is as high as 0.9 and the soft accuracy of the number of repetitions is higher than 90%.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 19 references that are in the map. First posted on arXiv 19 Jun 2023.

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6 of 19 references.

References · 6

  1. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  2. 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,162
  3. 2016RMPE: Regional Multi-person Pose Estimationcited by 340
  4. 2013DeepPose: Human Pose Estimation via Deep Neural Networkscited by 305
  5. 2020BlazePose: On-device Real-time Body Pose trackingcited by 113
  6. 2020Recognizing Exercises and Counting Repetitions in Real Timecited by 5

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