Determination of Gait Events and Temporal Gait Parameters for Persons with a Knee-Ankle-Foot Orthosis.

Gait event detection is essential for controlling an orthosis and assessing the patient's gait. In this study, patients wearing an electromechanical (EM) knee-ankle-foot orthosis (KAFO) with a single IMU embedded in the thigh were subjected to gait event detection. The algorithm detected four essential gait events (initial contact (IC), toe off (TO), opposite initial contact (OIC), and opposite toe off (OTO)) and determined important temporal gait parameters such as stance/swing time, symmetry, and single/double limb support. These gait events were evaluated through gait experiments using four force plates on healthy adults and a hemiplegic patient who wore a one-way clutch KAFO and a pneumatic cylinder KAFO. Results showed that the smallest error in gait event detection was found at IC, and the largest error rate was observed at opposite toe off (OTO) with an error rate of -2.8 ± 1.5% in the patient group. Errors in OTO detection resulted in the largest error in determining the single limb support of the patient with an error of 5.0 ± 1.5%. The present study would be beneficial for the real-time continuous monitoring of gait events and temporal gait parameters for persons with an EM KAFO.

High-Resolution Tactile-Sensation Diagnostic Imaging System for Thyroid Cancer.

In this study, we propose the direct diagnosis of thyroid cancer using a small probe. The probe can easily check the abnormalities of existing thyroid tissue without relying on experts, which reduces the cost of examining thyroid tissue and enables the initial self-examination of thyroid cancer with high accuracy. A multi-layer silicon-structured probe module is used to photograph light scattered by elastic changes in thyroid tissue under pressure to obtain a tactile image of the thyroid gland. In the thyroid tissue under pressure, light scatters to the outside depending on the presence of malignant and positive properties. A simple and easy-to-use tactile-sensation imaging system is developed by documenting the characteristics of the organization of tissues by using non-invasive technology for analyzing tactile images and judging the properties of abnormal tissues.

The Novel Digital Therapeutics Sensor and Algorithm for Pressure Ulcer Care Based on Tissue Impedance.

Visual diagnosis and rejuvenation are methods currently used to diagnose and treat pressure ulcers, respectively. However, the treatment process is difficult. We developed a biophotonic sensor to diagnose pressure ulcers and, subsequently, developed a pressure ulcer care device (PUCD.) We conducted animal and clinical trials to investigate the device's effectiveness. We confirmed the accuracy of the pressure ulcer diagnosis algorithm to be 91% and we observed an 85% reduction in immune cells when using the PUCD to treat pressure ulcer-induced mice. Additionally, we compared the treatment group to the pressure ulcer induction group to assess the PUCD's effectiveness in identifying immune cells through its nuclear shape. These results indicate a positive effect and suggest the use of PUCD as a recovery method for pressure ulcer diagnosis and treatment.

A Study of a Handrim-Activated Power-Assist Wheelchair Based on a Non-Contact Torque Sensor.

Demand for wheelchairs is increasing with growing numbers of aged and disabled persons. Manual wheelchairs are the most commonly used assistive device for mobility because they are convenient to transport. Manual wheelchairs have several advantages but are not easy to use for the elderly or those who lack muscular strength. Therefore, handrim-activated power-assist wheelchairs (HAPAW) that can aid driving power with a motor by detecting user driving intentions through the handrim are being researched. This research will be on HAPAW that judge user driving intentions by using non-contact torque sensors. To deliver the desired motion, which is sensed from handrim rotation relative to a fixed controller, a new driving wheel mechanism is designed by applying a non-contact torque sensor, and corresponding torques are simulated. Torques are measured by a driving wheel prototype and compared with simulation results. The HAPAW prototype was developed using the wheels and a driving control algorithm that uses left and right input torques and time differences are used to check if the non-contact torque sensor can distinguish users' driving intentions. Through this procedure, it was confirmed that the proposed sensor can be used effectively in HAPAW.