Abstract
Hand forces (HFs) are commonly measured during biomechanical assessment of manual materials handling; however, it is often a challenge to directly measure HFs in field studies. Therefore, in a previous study we proposed a HF estimation method based on ground reaction forces (GRFs) and body segment accelerations and tested it with laboratory equipment: GFRs were measured with force plates (FPs) and segment accelerations were measured using optical motion capture (OMC). In the current study, we evaluated the HF estimation method based on an ambulatory measurement system, consisting of inertial motion capture (IMC) and instrumented force shoes (FSs).Sixteen participants lifted and carried a 10-kg crate from ground level while 3D full-body kinematics were measured using OMC and IMC, and 3D GRFs were measured using FPs and FSs. We estimated 3D hand force vectors based on: (1) FP+OMC, (2) FP+IMC and (3) FS+IMC. We calculated the root-mean-square differences (RMSDs) between the estimated HFs to reference HFs calculated based on crate kinematics and the GRFs of a FP that the crate was lifted from.Averaged over subjects and across 3D force directions, the HF RMSD ranged between 10-15N when using the laboratory equipment (FP + OMC), 11-18N when using the IMC instead of OMC data (FP+IMC), and 17-21N when using the FSs in combination with IMC (FS + IMC). This error is regarded acceptable for the assessment of spinal loading during manual lifting, as it would results in less than 5% error in peak moment estimates.
| Original language | English |
|---|---|
| Pages (from-to) | 235-241 |
| Number of pages | 7 |
| Journal | Journal of Biomechanics |
| Volume | 70 |
| Early online date | 25 Oct 2017 |
| DOIs | |
| Publication status | Published - 21 Mar 2018 |
Funding
The authors thank Mr. Jacob Banks and Mr. Niall O’Brien at Liberty Mutual Research Institute for Safety for assistance during data collection. This work was supported by the European Union’s Horizon 2020 through the SPEXOR project, contract no. 687662 and partly by the Liberty Mutual – Harvard T.H. Chan School of Public Health postdoctoral program.
| Funders | Funder number |
|---|---|
| Harvard T.H. Chan School of Public Health | |
| Horizon 2020 Framework Programme | |
| Horizon 2020 | 687662 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Ergonomics
- Inertial measurement unit (IMU)
- Occupational biomechanics
- Spine
- Wearable sensors
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