EEG decoding with spatiotemporal convolutional neural network for visualization and closed-loop control of sensorimotor activities: A simultaneous EEG-fMRI study.

Closed-loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the associated behavioral performance. A spatiotemporal filter for high-density whole-head scalp EEG using a convolutional neural network can overcome the ambiguity of the signaling source because each EEG signal includes information on the remote regions. We simultaneously acquired EEG and functional magnetic resonance images in humans during the brain-computer interface (BCI) based neurofeedback training and compared the reconstructed and modeled hemodynamic responses of the sensorimotor network.

Investigating proficiency using a lift-type transfer support device for effective care: comparison of skilled and unskilled nursing homes.

Purpose: The purpose of the study was to investigate whether the sustained use of the "Hug," a "hugging" type robotic transfer support device, could increase the level of quality of care.

Methods: The effect of proficiency on using the device was examined in terms of time spent for transfer, ratio of transfers using the device, and range of targets. The results were compared between skilled care facilities that had used the device for >24 months and unskilled facilities.

Recognition capability of one's own skilled movement is dissociated from acquisition of motor skill memory.

When we have rehearsed a movement using an object, we can reproduce the movement without holding the object. However, the reproduced movement sometimes differs from the movement holding a real object, likely because movement recognition is inaccurate. In the present study, we tested whether the recognition capability was dissociated from the acquisition of motor skill memory.

Identification of care tasks for the use of wearable transfer support robots - an observational study at nursing facilities using robots on a daily basis.

Background: To reduce the physical burden of caregivers, wearable transfer support robots are highly desirable. Although these robots are reportedly effective for specific tasks in experimental environments, there is little information about their effectiveness at nursing care facilities. The aim of this study was to identify care tasks and operations suitable for the use of these robots among caregivers in nursing facilities where these robots have been in use on a daily basis.