ABSTRACT
BACKGROUND/AIM: Pinch and grip strength assessment is commonly performed in occupational therapy practice. However, the typically utilised methods are limited to pinch or grip dynamometers and do not readily translate to handling everyday objects. With the advent of consumer-grade 3D printing and low-cost sensor systems, the possibilities for creating customised assessment devices are expanding. As a first step in determining the validity of low-cost sensor systems, their data must be compared to a gold standard. Consequently, this study examined the criterion validity of two such systems for measuring pinch strength, specifically a small load cell and pressure-sensing fabric, with a mechanical pinch gauge. METHODS: A total of 33 participants performed strength tests using a mechanical pinch grip device, which had a plastic 3D printed cover with a pressure-sensing fabric overlaid on it to allow for simultaneous criterion validation, and a small load cell with a plastic 3D printed casing designed for comfortable pinch grip assessment. RESULTS: The simultaneously assessed fabric sensor and mechanical pinch grip device showed excellent absolute (ICC2,k = 0.94) and relative (Pearson's R = 0.90) agreement. Both devices showed similar excellent relative (R > 0.75) agreement with the load cell despite non-simultaneous assessment. These findings indicate that 3D printed sensors incorporating a load cell and a pressure-sensing fabric can be used to replicate a pinch grip assessment performed with a mechanical pinch gauge. CONCLUSIONS: This study lays the foundation for these sensor systems to be modified for use as assessment tools during the performance of functional tasks using everyday objects. Additionally, because both systems generate real-time force data they could be used for biofeedback as part of rehabilitation and strengthening programs. To aid uptake and future research using these systems, the 3D print models, step-by-step hardware design and software programs used are provided in an open-source format at www.rehabtools.org/otsensors.html.
