Publications by authors named "R Tozawa"
Article Synopsis
- * It involved 10 healthy older adults, 7 PD patients without FOG, and 7 PD patients with FOG, using a smartphone accelerometer to measure specific motion characteristics during one-leg standing.
- * Results showed that patients with PD and FOG had delayed peak latency and reduced peak magnitude in their movements, indicating greater impairment in anticipatory postural adjustments compared to those without FOG.
Objectives: Using smartphones, we aimed to clarify the characteristics of anticipatory postural adjustments (APA) in older adults and examine the relationship between cognitive and balance functions.
Methods: The study participants were 10 young and 13 older adults. An accelerometer built into a smartphone was attached to the lower back (L5) of the participant, and acceleration in the mediolateral direction was measured using a one-leg stance (OLS).
[Purpose] This study aimed to evaluate the reliability and validity of measuring the range of motion of joints using a remote videoconferencing system (Zoom) and a smartphone application. [Participants and Methods] This study included 16 young and healthy adults. The participants were instructed to perform shoulder joint flexion exercises in a seated position, with automatic motions, and maintain that posture throughout the measurement.
View Article and Find Full Text PDF[Purpose] This study aimed to investigate the reliability and validity of the quantitative evaluation of anticipatory postural adjustments using smartphones. [Participants and Methods] The study included 10 young control participants who underwent a one-legged stance with an accelerometer and a smartphone that were simultaneously attached to their lower back (L5). Acceleration was measured as the mediolateral component of the lumbar movement toward the stance side.
View Article and Find Full Text PDFBackground: The development of computer-assisted technologies to diagnose anterior cruciate ligament (ACL) injury by analyzing knee magnetic resonance images (MRI) would be beneficial, and convolutional neural network (CNN)-based deep learning approaches may offer a solution. This study aimed to evaluate the accuracy of a CNN system in diagnosing ACL ruptures by a single slice from a knee MRI and to compare the results with that of experienced human readers.
Methods: One hundred sagittal MR images from patients with and without ACL injuries, confirmed by arthroscopy, were cropped and used for the CNN training.