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Monitoring posture and movement accurately and efficiently is essential for both physical therapy and athletic training evaluation and interventions. Motion Tape (MT), a self-adhesive wearable skin-strain sensor made of piezoresistive graphene nanosheets (GNS), has demonstrated promise in capturing low back posture and movements. However, to address some of its limitations, this work explores alternative materials by replacing GNS with multi-walled carbon nanotubes (MWCNT). This study aimed to characterize the electromechanical properties of MWCNT-based MT. Cyclic load tests for different peak tensile strains ranging from 1% to 10% were performed on MWCNT-MT made with an aqueous ink of 2% MWCNT. Additional tests to examine load rate sensitivity and fatigue were also conducted. After characterizing the properties of MWCNT-MT, a human subject study with 10 participants was designed to test its ability to capture different postures and movements. Sets of six sensors were made from each material (GNS and MWCNT) and applied in pairs at three levels along each side of the lumbar spine. To record movement of the lower back, all participants performed forward flexion, left and right bending, and left and right rotation movements. The results showed that MWCNT-MT exceeded GNS-MT with respect to consistency of signal stability even when strain limits were surpassed. In addition, both types of MT could assess lower back movements. 

Background: Motion Tape (MT) is a low-profile, disposable, self-adhesive wearable sensor that measures skin strain. Preliminary studies have validated MT for measuring lower back movement. However, further analysis is needed to determine if MT can be used to measure lower back muscle engagement. The purpose of this study was to measure differences in MT strain between conditions in which the lower back muscles were relaxed versus maximally activated. Methods: Ten participants without low back pain were tested. A matrix of six MTs was placed on the lower back, and strain data were captured under a series of conditions. The first condition was a baseline trial, in which participants lay prone and the muscles of the lower back were relaxed. The subsequent trials were maximum voluntary isometric contractions (MVICs), in which participants did not move, but resisted the examiner force in extension or rotational directions to maximally engage their lower back muscles. The mean MT strain was calculated for each condition. A repeated measures ANOVA was conducted to analyze the effects of conditions (baseline, extension, right rotation, and left rotation) and MT position (1–6) on the MT strain. Post hoc analyses were conducted for significant effects from the overall analysis. Results: The results of the ANOVA revealed a significant main effect of condition (p < 0.001) and a significant interaction effect of sensor and condition (p = 0.01). There were significant differences in MT strain between the baseline condition and the extension and rotation MVIC conditions, respectively, for sensors 4, 5, and 6 (p = 0.01–0.04). The largest differences in MT strain were observed between baseline and rotation conditions for sensors 4, 5, and 6. Conclusions: MT can capture maximal lower back muscle engagement while the trunk remains in a stationary position. Lower sensors are better able to capture muscle engagement than upper sensors. Furthermore, MT captured muscle engagement during rotation conditions better than during extension.