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.

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.

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.

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.

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.

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.

Hand motion recognition based on forearm deformation measured with a distance sensor array.

Studies of upper limb motion analysis using surface electromyogram (sEMG) signals measured from the forearm plays an important role in various applications, such as human interfaces for controlling robotic exoskeletons, prosthetic hands, and evaluation of body functions. Though the sEMG signals have a lot of information about the activities of the muscles, the signals do not have the activities of the deep layer muscles. We focused on forearm deformation, since hand motion brings the muscles, tendons, and skeletons under the skin.