ArticleSensors (Basel, Switzerland)2023
A Wearable Multi-Modal Digital Upper Limb Assessment System for Automatic Musculoskeletal Risk Evaluation.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed.
- A Sensor-Based Upper Limb Treatment in Hemiplegic Patients: Results from a Randomized Pilot Study.Sensors (Basel, Switzerland) · 2024Trial
- Review
- Using a wearable system combining inertial and force sensing for simultaneous detection of limb motion and grasping actions in the workplace.Wearable technologies · 2025Article
- A Physical Fatigue Evaluation Method for Automotive Manual Assembly: An Experiment of Cerebral Oxygenation with ARE Platform.Sensors (Basel, Switzerland) · 2023Article
- The Association of the Job Involvement with Ergonomic Conditions and Mental Health in Staff of the Iranian Central Welfare Organization, Tehran, Iran.Indian journal of occupational and environmental medicineArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Continuous ergonomic risk assessment of the human body is critical to avoid various musculoskeletal disorders (MSDs) for people involved in physical jobs. This paper presents a digital upper limb assessment (DULA) system that automatically performs rapid upper limb assessment (RULA) in real-time for the timely intervention and prevention of MSDs. While existing approaches require human resources for computing the RULA score, which is highly subjective and untimely, the proposed DULA achieves automatic and objective assessment of musculoskeletal risks using a wireless sensor band embedded with multi-modal sensors. The system continuously tracks and records upper limb movements and muscle activation levels and automatically generates musculoskeletal risk levels. Moreover, it stores the data in a cloud database for in-depth analysis by a healthcare expert. Limb movements and muscle fatigue levels can also be visually seen using any tablet/computer in real-time. In the paper, algorithms of robust limb motion detection are developed, and an explanation of the system is provided along with the presentation of preliminary results, which validate the effectiveness of the new technology.
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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.