Skin Impedance Estimation System for Voltage-mode Electrical Stimulator with an AC Bridge Circuit.

Neuromuscular electrical stimulation is used to improve the motor function of paralyzed limbs and prevent muscle atrophy in stroke patients. The system for electrical stimulation is broadly classified into current-mode stimulators and voltage-mode stimulators. The current-mode stimulator adjusts the amplitude of the current, whereas the amplitude of the voltage is adjusted for voltage-mode stimulators. Voltagemode stimulators have the advantage that there is little risk of burns even if the electrode is partially detached. To perform arbitrary current-mode stimulation with voltage-mode stimulators, it is necessary to generate a stimulating voltage based on the skin impedance. As a primary experiment, the frequency characteristics of the electrode-skin impedance were measured using an impedance analyzer on 6 subjects, and the frequency band in which the skin impedance is equivalent to a parallel connection between resistance and capacitance was determined. A prototype bridge circuit with a skin impedance equivalent circuit implemented was designed, assembled, and tested to estimate the skin impedances of 3 subjects. The residuals were computed from the estimated skin-impedance resistance and capacitance of the bridge circuit, and the impedance-analyzer-measured resistance and capacitance. The residuals between the estimated and measured were up to 4.4 % in the resistance component, and up to 8.2 % in the capacitance component of the skin impedance measurements by the impedance analyzer.

Pleasant Stroke Touch on Human Back by a Human and a Robot.

Pleasant touching is an important aspect of social interactions that is widely used as a caregiving technique. To address the problems resulting from a lack of available human caregivers, previous research has attempted to develop robots that can perform this kind of pleasant touch. However, it remains unclear whether robots can provide such a pleasant touch in a manner similar to humans. To investigate this issue, we compared the effect of the speed of gentle strokes on the back between human and robot agents on the emotional responses of human participants (n = 28). A robot or a human stroked on the participants' back at two different speeds (i.e., 2.6 and 8.5 cm/s). The participants' subjective (valence and arousal ratings) and physiological (facial electromyography (EMG) recorded from the corrugator supercilii and zygomatic major muscles and skin conductance response) emotional reactions were measured. The subjective ratings demonstrated that the speed of 8.5 cm/s was more pleasant and arousing than the speed of 2.6 cm/s for both human and robot strokes. The corrugator supercilii EMG showed that the speed of 8.5 cm/s resulted in reduced activity in response to both human and robot strokes. These results demonstrate similar speed-dependent modulations of stroke on subjective and physiological positive emotional responses across human and robot agents and suggest that robots can provide a pleasant touch similar to that of humans.

Delivery of pleasant stroke touch via robot in older adults.

Touch care has clinically positive effects on older adults. Touch can be delivered using robots, addressing the lack of caregivers. A recent study of younger participants showed that stroke touch delivered via robot produced subjective and physiologically positive emotional responses similar to those evoked by human touch. However, whether robotic touch can elicit similar responses in older adults remains unknown. We investigated this topic by assessing subjective rating (valence and arousal) and physiological signals [corrugator and zygomatic electromyography (EMG) and skin conductance response (SCR)] to gentle stroking motions delivered to the backs of older participants by robot and human agents at two different speeds: 2.6 and 8.5 cm/s. Following the recent study, the participants were informed that only the robot strokes them. We compared the difference between the younger (their data from the previous study) and the older participants in their responses when the two agents (a robot and a human) stroked them. Subjectively, data from both younger and older participants showed that 8.5 cm/s stroking was more positive and arousing than 2.6 cm/s stroking for both human and robot agents. Physiologically, data from both younger and older participants showed that 8.5 cm/s stroking induced weaker corrugator EMG activity and stronger SCR activity than the 2.6 cm/s stroking for both agents. These results demonstrate that the overall patterns of the older groups responses were similar to those of the younger group, and suggest that robot-delivered stroke touch can elicit pleasant emotional responses in older adults.

Analysis of Skin Deformation Differences on the Upper Arm Between Active and Passive Movements During Elbow Flexion and Extension.

The motion ability of patients in the acute phase of stroke is difficult to define with existing indexes such as the Brunnstrom stage. Hence, for designing a novel evaluation index for stroke rehabilitation in the acute phase, we focused on the differences between the skin deformations in active and passive movements. Skin deformation reflects the activities of body tissues that are related to motion ability. We measured skin deformations on the upper arm in active and passive movements during elbow flexion and extension and extracted features from these deformations. For practical rehabilitation applications, we developed a novel flexible distance sensor array to reduce the time needed for attaching sensors to patients. Using principal component analysis (PCA), the skin deformation could be decomposed into joint movements and activeness of movements as the first two components (PC1 and PC2). The joint angle and PC1 exhibited a high correlation, and the standard deviation (SD) of PC2 indicated a significant difference in the types of movements. From the above results, we concluded that the SD ratio between PC2 and PC1 may be used to evaluate motion ability considering the inherent biomechanical characteristics.

A Quantitative Measurement of Hand Scaling Motion for Dental Hygienist Training.

In dental hygienist education, many skills are taught that cannot be acquired without repeated training. To make this training more efficient, we need to measure the students' skills and show correction points in real-time. In this research, we focus on hand scaling work, which is one of the most important tasks of dental hygienists. We developed a measurement system to measure both the motion and force exerted during hand scaling work. This measured data can be used to quantitatively evaluate students' skills. In the experiment, we measured the hand scaling motion of several participants with different levels of job experience, including dental hygienist teachers, dental hygienists, and dental hygienist students. We showed that it is possible to extract from the measured results a quantitative index for discriminating different individual skills.

Prediction of Plantar Forces During Gait Using Wearable Sensors and Deep Neural Networks.

To enable on-time and high-fidelity lower-limb exoskeleton control, it is effective to predict the future human motion from the observed status. In this research, we propose a novel method to predict future plantar force during the gait using IMU and plantar sensors. Deep neural networks (DNN) are used to learn the non-linear relationship between the measured sensor data and the future plantar force data. Using the trained network, we can predict the plantar force not only during walking but also at the start and end of walking. In the experiments, the performance of the proposed method is confirmed for different prediction time.