ArticleArabian journal for science and engineering2023
A New Home-Based Upper- and Lower-Limb Telerehabilitation Platform with Experimental Validation.
Article in Arabian journal for science and engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 22 citations in OpenAlex.
- Efficient Thermal Pose Estimation: Balancing Accuracy and Edge Deployment for Smart Home Activity Recognition.Sensors (Basel, Switzerland) · 2026Article
- A Novel Hand Teleoperation Method with Force and Vibrotactile Feedback Based on Dynamic Compliant Primitives Controller.Biomimetics (Basel, Switzerland) · 2025Article
- Assistance Device Based on SSVEP-BCI Online to Control a 6-DOF Robotic Arm.Sensors (Basel, Switzerland) · 2024Article
- Telerehabilitation to Address the Rehabilitation Gap in Anterior Cruciate Ligament Care: Survey of Physical Therapists/Care Providers.Telemedicine reports · 2024Article
- Impact of AI-Powered Solutions in Rehabilitation Process: Recent Improvements and Future Trends.International journal of general medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The world is witnessing interesting challenges in several fields, including medicine. Solutions to many of these challenges are being developed in the field of artificial intelligence. As a result, artificial intelligence techniques can be used in telerehabilitation to facilitate the work of doctors and to find methods that can be used to better treat methods that can be used to better treat patients. Motion rehabilitation is an essential procedure for elderly people and patients undergoing physiotherapy after physical procedures such as surgery for the anterior cruciate ligament (ACL), a frozen shoulder. To regain normal motion, the patient must participate in rehabilitation sessions. Furthermore, telerehabilitation has become a significant trend in research studies because of the COVID-19 pandemic, which is continuing to affect the world through the delta and the omicron variants, and other epidemics. In addition, because of other special issues like the vastness of the desert area in Algeria and the lack of facilities, it is ideal to avoid requiring patients to travel for all of their rehabilitation sessions; patients should be able to perform their rehabilitation exercises at home. Thus, telerehabilitation could lead to promising developments in this field. Therefore, our project's goal is to develop a website for telerehabilitation that can be used to facilitate rehabilitation from a distance. We also want to track the progress of patients' range of motion (ROM) in real time using artificial intelligence techniques, by controlling the angles of the motion of a limbs about a joint.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.