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Abstract Squatting is an intensive activity routinely performed in the workplace to lift and lower loads. The effort to perform a squat can decrease using an exoskeleton that considers individual worker’s differences and assists them with a customized solution, namely, personalized assistance. Designing such an exoskeleton could be improved by understanding how the user’s muscle activity changes when assistance is provided. This study investigated the change in the muscle recruitment and activation pattern when personalized assistance was provided. The personalized assistance was provided by an ankle–foot exoskeleton during squatting and we compared its effect with that of the no-device and unpowered exoskeleton conditions using previously collected data. We identified four main muscle recruitment strategies across ten participants. One of the strategies mainly used quadriceps muscles, and the activation level corresponding to the strategy was reduced under exoskeleton assistance compared to the no-device and unpowered conditions. These quadriceps dominant synergy and rectus femoris activations showed reasonable correlations (r = 0.65, 0.59) to the metabolic cost of squatting. These results indicate that the assistance helped reduce quadriceps activation, and thus, the metabolic cost of squatting. These outcomes suggest that the muscle recruitment and activation patterns could be used to design an exoskeleton and training methods. 

The foot center of pressure (COP) variability is an important indicator of balance, particularly relevant for rehabilitation and training using wearable lower limb exoskeletons. This study aimed to evaluate the effectiveness of our exoskeleton in assisting squatting motion using the COP variability as a metric. Six human subjects performed alternate squatting and standing movements while their foot pressure and COP trajectories were recorded using insole pressure sensors. The exercises were performed under three conditions: i) no device, ii) unpowered device, and iii) device with optimal stiffness. Results showed that the variability of the COP trajectory in the anterior-posterior direction of the foot during squatting tended to be lower for the optimal stiffness condition than the no device and unpowered device conditions, indicating the potential usefulness of the device in improving balance during squatting. This study has implications for human-inthe-loop optimization and balance control of the exoskeleton based on COP. 

Abstract Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information. The physical effort represents the work hardness used to optimize wearable robotic systems. Thus, personalization and rapid optimization of the effort are critical. Although respirometry is the gold standard for estimating metabolic costs, this method requires a heavy, bulky, and rigid system, limiting the system’s field deployability. Here, this paper reports a soft, flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton, used to estimate metabolic costs and physical effort, demonstrating the potential for real-time wearable robot adjustments based on biofeedback. Data from a set of activities, including walking, running, and squatting with the biopatch and exoskeleton, determines the relationship between metabolic costs and heart rate variability root mean square of successive differences (HRV-RMSSD) (R = −0.758). Collectively, the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.