Effective evaluation of HGcnMLP method for markerless 3D pose estimation of musculoskeletal diseases patients based on smartphone monocular video.

Markerless pose estimation based on computer vision provides a simpler and cheaper alternative to human motion capture, with great potential for clinical diagnosis and remote rehabilitation assessment. Currently, the markerless 3D pose estimation is mainly based on multi-view technology, while the more promising single-view technology has defects such as low accuracy and reliability, which seriously limits clinical application. This study proposes a high-resolution graph convolutional multilayer perception (HGcnMLP) human 3D pose estimation framework for smartphone monocular videos and estimates 15 healthy adults and 12 patients with musculoskeletal disorders (sarcopenia and osteoarthritis) gait spatiotemporal, knee angle, and center-of-mass (COM) velocity parameters, etc.

A Precise Hip Protection System with Multi-scale Fall Warning Algorithm Based on Offset Displacement.

Falls occur frequently in daily life and the damage to the body is irreversible. Therefore, it is crucial to implement timely and effective warning and protection systems for falls to minimize the damage caused by falls. Currently, the fall warning algorithm has shortcomings such as low recognition rates for falls and fall-risk movements and insufficient lead-time, the time before the subject impacts the floor, making it difficult for falling protection devices to function effectively.

A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement.

Knee osteoarthritis is a degenerative disease, which greatly affects the daily life of patients. Total knee replacement (TKR) is the most common method to treat knee joint disorders and relieve knee pain. Postoperative rehabilitation exercise is the key to restore knee joint function.

Real-time Action Recognition and Fall Detection Based on Smartphone.

This paper presents a smartphone application which has realized action recognition and fall detection. The application identifies the holding pattern of smartphone by the data of light sensor, distance sensor and accelerometer sensor, which reduce the impact of recognition resulting from the smartphone's different positions. And then the application uses data collected from the acceleration sensor, the direction angle sensor and the gyro sensor to distinguish fall from daily actions.

Pre-impact Alarm System for Fall Detection Using MEMS Sensors and HMM-based SVM Classifier.

Accidental fall can cause physical injury, fracture and other health complication, especially for elderly people living alone. Aimed to provide timely assistance after the occurrence of falling down, a pre-fall alarm system was proposed. In order to test the reliability of pre-fall alarm system, eighteen subjects who worn this device on the waist were required to participate in a series of experiments.

Unexpected catalytic performance of Fe-M-C (M = N, P, and S) electrocatalysts towards oxygen reduction reaction: surface heteroatoms boost the activity of FeM/graphene nanocomposites.

The rational design of non-noble materials as low-cost, highly efficient, and durable catalysts to improve the oxygen reduction reaction is extremely urgent and challenging. The oxygen reduction reaction is a kinetically sluggish process that greatly affects the energy conversion efficiency. In this paper, novel hierarchical heteroatoms-co-doped FeM/graphene (M = P, N) nanocomposites were developed by a facile strategy, including hydrothermal and subsequent calcination methods.

A MAC protocol with high scalability for motion capture based on frequency division multiple and time division multiple access.

A good performance of motion capture, which belongs to body sensor network, depends on a reasonable design of MAC protocol. The purpose of this study is to design a reliable and highly extensible protocol for applying in motion capture. The proposed MAC protocol can easily be actualized by the timer in the chip.

Phosphorus and Fluorine Co-Doping Induced Enhancement of Oxygen Evolution Reaction in Bimetallic Nitride Nanorods Arrays: Ionic Liquid-Driven and Mechanism Clarification.

Electrocatalytic splitting of water is becoming increasingly crucial for renewable energy and device technologies. As one of the most important half-reactions for water splitting reactions, the oxygen evolution reaction (OER) is a kinetically sluggish process that will greatly affect the energy conversion efficiency. Therefore, exploring a highly efficient and durable catalyst to boost the OER is of great urgency.

Relationship between dynamical characteristics of sit-to-walk motion and physical functions of elderly humans.

Sit-to-walk (STW) motion is essential for daily activities. Falls frequently occur, when there is impaired ability to perform STW movements. This study investigated the relationships between the dynamical characteristics of STW motion and physical functions of elderly people.

Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms.

The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF) data, which was quantified by sample entropy, was collected by foot force sensors.

Exploration and comparison of the pre-impact lead time of active and passive falls based on inertial sensors.

Research on falls in elderly people has a great social significance because of the rapidly growing of the aging population. The pre-impact lead time of fall (PLT) is an important part of the human fall theory. PLT is the longest time for a person who is going to fall to take action in order to prevent the fall or to reduce bodily injuries from the fall impact.