A5076701387- Stroke Rehabilitation and Recovery
- Botulinum Toxin and Related Neurological Disorders
- Chronic Obstructive Pulmonary Disease (COPD) Research
- ECG Monitoring and Analysis
- Hemodynamic Monitoring and Therapy
- Statistical Methods in Epidemiology
- Phonocardiography and Auscultation Techniques
- Non-Invasive Vital Sign Monitoring
- Acute Ischemic Stroke Management
- Muscle activation and electromyography studies
University of Science and Technology of China
2022
Suzhou Institute of Biomedical Engineering and Technology
2022
Chinese Academy of Sciences
2022
Millimeter Wave(mmWave) radar has been widely used in vital sign monitoring with non-contact and privacy protection. To reduce the effect of random body motion, respiration, its harmonics on heart rate estimation, based frequency-modulated continuous-wave (FMCW) is researched this paper. First, a signal extraction algorithm designed for Range Bin variation caused by motion heavy breathing. Second, heartbeat Adaptive Notch Filter (ANF) Empirical Wavelet Transform (EWT). The harmonic...
Rehabilitation training and movement evaluation after stroke have become a research hotspot as has very common harmful disease. However, traditional rehabilitation are mainly conducted under the guidance of doctors. The process is time-consuming results greatly influenced by In this study, desktop upper limb robot was designed quantitative system motor function for patients proposed. kinematics dynamics data during active were collected sensors. Combined with scores patients' doctors using...
Motor function evaluation is a significant part of post-stroke rehabilitation protocols, and the wrist motor helps provide patients with individualized training programs. However, traditional assessment coarsely graded, lacks quantitative analysis, relies heavily on clinical experience. In order to objectively quantify dysfunction in stroke patients, novel system based force feedback machine learning algorithm was proposed. Sensors embedded force-feedback robot record kinematic movement data...
The World Health Organization has projected that by 2030, chronic obstructive pulmonary disease (COPD) will be the third-leading cause of mortality and seventh-leading morbidity worldwide.[1] Acute exacerbations (AECOPD) are associated with an accelerated decline in lung function, diminished quality life, higher mortality.[2] Accurate early detection AECOPD contributes to better management reduction, recent past there been great progress development application machine learning (ML), which...