Digital Markers of Mobility in Daily Life to Track Progression in Newly Diagnosed Parkinson's Disease

日常生活中的移动数字标记可追踪新诊断的帕金森病的进展

• 批准号: 10708151
• 负责人: Martina Mancini
• 金额: $ 61.86万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708151
• 关键词: Affect; Algorithm Design; Characteristics; Clinic; Clinical; Clinical Trials; Collaborations; Communities; Complex; Data; Data Analyses; Development; Diagnosis; Digital biomarker; Disease; Disease Marker; Disease Progression; Elderly; Environment; Equilibrium; Evaluation; Expert Opinion; Functional disorder; Future; Gait; Home; Idiopathic Parkinson Disease; Intervention; Laboratories; Life; Linear Regressions; Measures; Methods; Modeling; Motor; Movement Disorder Society Unified Parkinson' s Disease Rating Scale; Neurodegenerative Disorders; Neurologist; Newly Diagnosed; Outcome; Outcome Measure; Parkinson Disease; Participant; Patient Outcomes Assessments; Patients; Performance; Persons; Posture; Prognosis; Quality of life; Reporting; Severity of illness; Testing; Time; Tremor; Walking; clinical decision-making; clinical outcome measures; clinical practice; diaries; digital measure; disability; disease phenotype; effectiveness testing; fall risk; falls; foot; improved; instrument; multitask; neuroprotection; neuroregulation; novel; prevent; prospective; sensor; sensor technology; sex; wearable device; wearable sensor technology

Project Summary/Abstract A critical limitation in development of disease-modifying interventions for Parkinson's disease (PD) and other neurodegenerative diseases is the lack of reliable, objective measures of disease progression. Walking and turning dysfunction appear early in Parkinson's disease and use of inertial sensors to measure walking and turning may provide sensitive, objective markers of disease progression as well as of decline in quality of life. New wearable technology can provide reliable, objective measures of walking and turning that are feasible for clinical trials. However, quantifying walking and turning during unsupervised, daily life has the untapped potential to provide objective measures that are even more sensitive to disease progression, to quality of life and fall risk than current subjective clinical measures of mobility. We predict that turning quality may be even more sensitive to progression of disease in early PD, than straight walking because of the added dynamic balance challenges. Aim I will determine the most sensitive measures of mobility (daily life) in 100 people with early, untreated PD and 50 older control subjects. We hypothesize that unsupervised daily life mobility measures will be sensitive and specific for early PD. Aim II will determine the measures of mobility in daily life most sensitive to disease progression. We hypothesize that turning characteristics during daily life (particularly variability of performance) will be the most sensitive mobility measures to change over 3 years in recently diagnosed people with PD. Aim III will predict future falls based on daily life objective measures of walking and turning. We hypothesize that objective measures of daily life gait and turning quality will significantly improve prediction of who will fall and time-to-first-fall compared to clinical measures (i.e., fall risk). Identification of the most sensitive set of measures of mobility disability progression during real life activities with wearable technology will provide quantifiable and objective outcome measures for testing the effectiveness of new disease-modifying therapies. Improved prognosis of mobility decline will also improve timing of clinical interventions.

项目总结/文摘