Ergonomic risk factors and work-related musculoskeletal disorders in clinical physiotherapy

Abstract

Objectives: The purpose of this study was to objectively quantify and evaluate the ergonomic risk of clinical physiotherapy practices and evaluate physiotherapists for work-related musculoskeletal disorders and pain.

Methods: Twenty-nine physiotherapists in the rehabilitation department of a large-scale tertiary hospital were recruited in this study. The sampling period lasted for 2 weeks for each physiotherapist and interval sampling was adopted to avoid duplication of cases. Therapist posture during physiotherapy was captured, tracked and analyzed in real time using structured light sensors with an automated assessment program. The quantification of ergonomic risk was based on REBA (Rapid Entire Body Assessment) and the RPE (perceived physical exertion) scores of the therapists were recorded before and after treatment, respectively.

Results: Two hundred and twenty-four clinical physiotherapy cases were recorded, of which 49.6% were high risk and 33% were very high risk, with none of the cases presenting negligible risk. The positioning (p < 0.001) of physiotherapist had a considerable impact on ergonomic risk and pediatric physiotherapy presented a higher risk to physiotherapists than adults (p < 0.001). The RPE score of physiotherapist after performing physiotherapy was greater than before physiotherapy and was positively correlated with the REBA distribution.

Conclusion: Our study creates an automatic tool to assess the ergonomic risk of physiotherapy practices and demonstrates unacceptable ergonomic risk in common practices. The high prevalence of musculoskeletal disorders and pains recommends that rehabilitation assistance devices should be optimized and standard ergonomic courses should be included in physiotherapists' training plans.

Keywords: Kinect; Rapid Entire Body Assessment (REBA); ergonomic assessment; occupational health and safety; physiotherapist.

Figure 1

(A) Capturing the therapist's posture by Kinect. The leftmost of (A) represents the real environment in which physiotherapy is being performed. The middle is the sensor-Azure Kinect, and the rightmost is the modeling of the skeleton of the physiotherapist (B). Example Rapid Entire Body Assessment (REBA) scoring for a physiotherapy.

Figure 2

Flowchart: after conducting the inclusion and exclusion of operational cases, 224 cases were included in analysis. Objective assessment was carried out in these cases to collect data from both physiotherapists and patients, followed by a subjective assessment including the demographic information and the body-parts and duration of pain of physiotherapists.

Figure 3

Procedures of automatic ergonomics assessment tools. Once Kinect has scanned the spatial environment and the person, the researcher can select the person index to capture the motion of the specified person within the scene. Confirming the capture object, the automated algorithm will calculate the angle value based on the bone joints and bone length, which finally corresponds to the REBA score “+” (The REBA score is a combination of REBA Table A and REBA Table B). The generated data will be saved to the local port in real time.

Figure 4

Boxplot displaying the REBA score by physiotherapy on child or adult (A), Physiotherapists positioning (B). The Y-axis is the REBA score and X-axis is the types of parameters .