Publications by authors named "Mikaela L Frechette"
Article Synopsis
- The study focuses on creating an automated fall detection algorithm specifically for wheelchair users, addressing the lack of such devices.
- Researchers used machine learning techniques and data from accelerometers on participants to distinguish between actual falls and wheelchair-related movements.
- The algorithm showed high accuracy rates (100% for wrist data) and is recommended for integration into a wrist-worn device for real-world testing among wheelchair users.
Article Synopsis
- The study aimed to compare heart rate, oxygen consumption, blood lactate, and perceived exertion in arm cycling with and without blood flow restriction.
- Twelve healthy males participated in four different arm cycling conditions, including high-workload and low-workload with blood flow restriction, measuring various physiological responses during and after the exercises.
- Results showed that high-workload cycling produced the most significant physiological responses, suggesting that increasing exercise intensity is more effective than using blood flow restriction for improving arm cycling performance.
Falls are a prevalent and serious health concern across clinical populations. A critical step in falls prevention is identifying modifiable risk factors, but due to time constraints and equipment costs, fall risk screening is rarely performed. Mobile technology offers an innovative approach to provide personalized fall risk screening for clinical populations.
View Article and Find Full Text PDFBackground: Falls are common, detrimental events among ambulatory individuals with spinal cord injury (SCI). Following SCI, changes to lower limb function are probable and likely to impact an individual's fall risk, yet no comprehensive review has been completed on the topic.
Objectives: This study systematically reviewed data on the relationship between lower limb function and fall prevalence in ambulatory individuals with SCI.
Chronic progressive neurodegenerative diseases (NDD) cause mobility and cognitive impairments that disrupt quality of life. The learning of new motor skills, motor learning, is a critical component of rehabilitation efforts to counteract these chronic progressive impairments. In people with NDD, there are impairments in motor learning which appear to scale with the severity of impairment.
View Article and Find Full Text PDFBackground: Public health responses to Coronavirus Disease 2019 (COVID-19) including lockdowns may negatively impact physical and mental functioning in clinical populations. People living with multiple sclerosis (MS) may be more susceptible to physical function deterioration while practicing social distancing. Recent reports have suggested that about 50% of people with MS (pwMS) decreased their leisure physical activity during COVID-19, and upwards of 30% reported decreased physical fitness levels.
View Article and Find Full Text PDFA reliable fall detection device is crucial to minimize long-term consequences of falls among wheelchair users. This study examines the sensitivity of Apple Watch to detect intentional falls from a wheelchair. Twenty-five able bodied (age: 21.
View Article and Find Full Text PDFThe aim of this study was to investigate the feasibility and preliminary validity and reliability of remote sitting balance assessment. Seven wheelchair users (mean age: 42.7 ± 19.
View Article and Find Full Text PDFSeated postural control is essential for wheelchair users to maintain proper position while performing activities of daily living. Clinical tests are commonly used to measure seated postural control, yet they are subjective and lack sensitivity. Lab-based measures are highly sensitive but are limited in scope and restricted to research settings.
View Article and Find Full Text PDFNext Steps in Wearable Technology and Community Ambulation in Multiple Sclerosis.
Curr Neurol Neurosci Rep
September 2019
Article Synopsis
- Walking issues are common in people with multiple sclerosis (PwMS), impacting their quality of life and typically measured using self-reports and clinical tests that may not capture real-world walking fully.
- Wearable sensors, which can objectively assess various aspects of walking and provide data from everyday life, are under-researched in PwMS compared to other populations like older adults.
- Current studies have begun to use wearable tech but have mostly focused on pace, with limited exploration of important gait characteristics like variability, asymmetry, and complexity during daily activities, indicating a need for further research in this area.*