Recognizing human movement intention is key to control wearable robotics for assistance such as in the elderly and rehabilitation. Piezoelectric sensors, in particular highly sensitive ferroelectrets (FEs), qualify for the assessment of subtle muscle movements using force myography (FMG). In contrast to electromyography (EMG), which measures electrical muscle activity, FMG measures the mechanical muscle response to overcome issues in electrode placement and skin preparation. We employ 3D-printed polypropylene FE sensor patches for FMG adjacent to EMG electrodes as a reference at the lower limb of six young unimpaired participants performing sit-to-stand movements. The activity onsets of FMG and EMG are systematically compared at the quadriceps femoris and visually verified using a high-speed camera. The average time difference (35 $\pm$ 50 ms) aligns with the known electromechanical muscle delay. Notably, our results demonstrate that FMG can provide an early indicator for the activity onset significantly before the EMG (on average 263 $\pm$ 90 ms earlier) in this scenario due to the possibility to measure passive muscle deformation. In addition, the signal-to-noise ratio (SNR) of the FE signal (53 dB) exceeds that of the EMG (39 dB) during the maximum muscle activity, while the average variability is slightly larger for FE (22%) compared to EMG (17%). In conclusion, our customizable FE sensors prove to be suitable for motion intention detection and promise an advance in wearable assistive devices, such as active prostheses and exoskeletons, to support people in need.

Plantar pressure measurement, or pedobarography, is an essential tool for analyzing human motion in healthy individuals and patients. Across the reviewed literature, sensor insoles are motivated as wearable, mobile solutions for assessing pressure distribution in applications including diabetic foot monitoring, rehabilitation guidance, assistive device control, and sports performance analysis. This review evaluates the current state of the art with particular attention to sensor technologies, sensor quantity and placement, participant cohorts, and reference standards. The focus lies on original works with innovative designs, preferably supported by ambulation experiments. The modalities covered include resistive, capacitive, inductive, piezoelectric, triboelectric, and optical sensing approaches. We identify a lack of proper sensor calibration, gait-based verification, and human study validation, and propose a gold standard based on testing machines and instrumented treadmills to ensure comparability across studies. The bidirectional interaction between insole insertion and foot-sole mechanics is examined, with tissue stiffness identified as a key source of uncertainty in sensor signals. Guidelines are provided for sensor dimensions and unobtrusive insole designs to foster natural gait. Finally, future directions include the development of multimodal sensors to compensate for limitations of individual modalities and the emerging trend of multiaxial sensing for capturing shear components in pressure distributions.

Haptic motion guidance has the potential to advance assistive technologies that support humans in movement tasks. This study systematically evaluates wrist rotation guidance methods in a 2×2 repeated measures design using a wearable vibrotactile feedback device. In two tasks, we investigate the benefits of encoding the current target distance in the cue strength and conveying additional information about the target location by incorporating a tactile illusion known as phantom sensation. For a directional response task, we analyze reaction times and error rates, and for an angle targeting task, we examine rise time, settling time, and maximum overshoot of the normalized step responses. These objective criteria are complemented by subjective user ratings that assess the intuitiveness and ease of interpreting the vibrotactile cues. Feedback methods incorporating an adaptive amplitude perform significantly better in the angle targeting task compared to those using a constant amplitude. Additional improvements can be achieved by combining the adaptive amplitude with phantom sensations, including an average additional 24.3% reduction in rise time. Furthermore, more than half of the participants rate this combination as their favorite method. Altogether, the results underline the potential of incorporating phantom sensations in vibrotactile wrist guidance, thereby contributing to the advancement of wearable haptics in assistive applications.

Precise and portable ground reaction force (GRF) measurement is critical for advancing biomechanical gait analysis and enabling more effective control of robots and assistive devices. This study investigates vertical GRF estimation during walking using a soft, lightweight, and cost-effective 3D-printed ferroelectret insole. The insole design incorporates four monolithically 3D-printed piezoelectric sensors positioned under key foot contact areas, which generate nonlinear voltage in response to applied forces. A 1-D convolutional neural network (CNN), featuring two convolutional and two fully connected layers, was trained to predict vertical GRF across five different walking speeds (50–150% of normal walking speed). The CNN was validated using K-fold cross-validation, enhancing model generalization. Results showed an average root-mean-squared error of 9.24% and $R^{2}$ values exceeding 0.99 across different speeds, demonstrating the potential of 3D-printed ferroelectret sensors for portable GRF measurement in gait analysis and robotics applications.

Background/Objectives: This study investigated the biomechanics of a hip exoskeleton during sit-to-stand transitions. Methods: Eleven participants performed the task under three conditions: without the exoskeleton (No Exo), wearing the exoskeleton without assistance (Exo Off), and wearing it with hip extension assistance (Exo On). Results: The analyses revealed that joint angles (hip, knee, and ankle) and vertical ground reaction forces were comparable across all conditions. However, Exo Off significantly increased transition time, whereas Exo On did not differ significantly from No Exo. Additionally, both exoskeleton conditions led to increased integrated EMG (iEMG) activity in the rectus femoris, vastus medialis, and gluteus maximus—likely due to the added device mass. Notably, iEMG analysis revealed a significant reduction in gluteus maximus activity in Exo On compared to Exo Off. Conclusions: Despite providing only moderate torque assistance (0.12 Nm/kg), the results suggest that well-timed exoskeleton support can partially reduce the physical demands of sit-to-stand transitions. However, the observed reduction in gluteus maximus activity was limited, likely reflecting the combined effects of the assistance strategy, including its magnitude and timing, user adaptation and training, postural demands due to device weight and external torques, and mechanical constraints such as potential joint misalignment. Further research is needed to optimize hip exoskeleton support for daily activities.