A5069801136- Balance, Gait, and Falls Prevention
- Parkinson's Disease Mechanisms and Treatments
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Cardiovascular and exercise physiology
- Cerebral Palsy and Movement Disorders
- Physical Activity and Health
- Gait Recognition and Analysis
- Neurological disorders and treatments
- Indoor and Outdoor Localization Technologies
- Diabetic Foot Ulcer Assessment and Management
- Spine and Intervertebral Disc Pathology
- Scoliosis diagnosis and treatment
- Hand Gesture Recognition Systems
- Frailty in Older Adults
- Space Exploration and Technology
- Space exploration and regulation
- Nuclear Issues and Defense
- Spondyloarthritis Studies and Treatments
- Muscle activation and electromyography studies
AbbVie (United States)
2023-2024
University of Rochester Medical Center
2023
Takeda (Japan)
2023
University of Rochester
2023
Pfizer (United States)
2019-2022
Kennedy Space Center
2017
Technological advances in multimodal wearable and connected devices have enabled the measurement of human movement physiology naturalistic settings. The ability to collect continuous activity monitoring data with digital real-world environments has opened unprecedented opportunity establish clinical phenotypes across diseases. Many traditional assessments physical function utilized trials are limited because they episodic, therefore, cannot capture day-to-day temporal fluctuations...
Abstract Background Digital health technologies show promise for improving the measurement of Parkinson’s disease in clinical research and trials. However, it is not clear whether digital measures demonstrate enhanced sensitivity to progression compared traditional approaches. Methods To this end, we develop a wearable sensor-based algorithm deriving features upper lower-body bradykinesia evaluate 1-year longitudinal using data from WATCH-PD study, multicenter, observational assessment study...
Czech et al., (2019). GaitPy: An Open-Source Python Package for Gait Analysis Using an Accelerometer on the Lower Back. Journal of Open Source Software, 4(43), 1778, https://doi.org/10.21105/joss.01778
Wearable inertial sensors are providing enhanced insight into patient mobility and health. Significant research efforts have focused on wearable algorithm design deployment in both clinical settings; however, open-source, general-purpose software tools for processing various activities of daily living relatively scarce. Furthermore, few studies include code replication or off-the-shelf packages. In this work, we introduce SciKit Digital Health (SKDH), a Python package (Python Software...
Measuring free-living gait using wearable devices may offer higher granularity and temporal resolution than the current clinical assessments for patients with Parkinson disease (PD). However, increasing number of worn on body adds to patient burden impacts compliance.This study aimed investigate impact reducing ability assess impairments in PD.A total 35 volunteers PD 60 healthy performed a task during 2 clinic visits. Participants were assessed On Off medication state Movement Disorder...
Traditional measurement systems utilized in clinical trials are limited because they episodic and thus cannot capture the day-to-day fluctuations longitudinal changes that frequently affect patients across different therapeutic areas.The aim of this study was to collect evaluate data from multiple devices, including wearable sensors, compare them standard lab-based instruments domains daily tasks.Healthy volunteers aged 18-65 years were recruited for a 1-h assess sensors. They performed...
Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Climb Power Test (SCPT). This method subject to human error and cannot provide continuous remote monitoring. Continuous monitoring using wearable sensors may more comprehensive assessment lower-limb function. In this work, we propose an algorithm classify stair climbing periods estimate SCP from lower-back worn accelerometer, which strongly agrees with standard (r = 0.92, p < 0.001; ICC 0.90,...
<sec> <title>BACKGROUND</title> Measuring free-living gait using wearable devices may offer higher granularity and temporal resolution than the current clinical assessments for patients with Parkinson disease (PD). However, increasing number of worn on body adds to patient burden impacts compliance. </sec> <title>OBJECTIVE</title> This study aimed investigate impact reducing ability assess impairments in PD. <title>METHODS</title> A total 35 volunteers PD 60 healthy performed a task during 2...
Axial spondyloarthritis is a chronic inflammatory disease that primarily affects the axial skeleton. Spinal inflammation, back pain and new bone formation contribute to progressive impairment of spinal mobility. Measuring Range Motion (SRoM) important assess pathology, monitor activity, guide treatment decisions, determine responses. Standard care, distance-based angular-based clinical measurements, have several limitations, including subjectivity, inter-assessor variability, low...
Abstract Digital health technologies show promise for improving the measurement of Parkinson’s disease in clinical research and trials. However, it currently isn’t clear whether digital measures demonstrate enhanced sensitivity to progression compared traditional approaches. To this end, we develop a wearable sensor-based algorithm deriving features upper lower-body bradykinesia establish validity by investigating convergent with appropriate constructs, known groups validity, test-retest...
<sec> <title>UNSTRUCTURED</title> Wearable inertial sensors are providing enhanced insight into patient mobility and health. Significant research efforts have focused on wearable algorithm design deployment in both clinical settings; however, open-source, general-purpose software tools for processing various activities of daily living relatively scarce. Furthermore, few studies include code replication or off-the-shelf packages. In this work, we introduce SciKit Digital Health (SKDH), a...