An Objective Assessment Tool for Evaluating Functioning in Older Adults
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 30
- 试验地点
- 1
- 主要终点
- develop an automated analysis of the SPPB clinical tests
研究概览
简要总结
The Investigators are seeking your consent to participate in research investigating the development of a mobile application that enhances physical and cognitive assessments.
This is in response to the growing significance of the Short Physical Performance Battery (SPPB) in Alzheimer's Disease and Related Dementias (AD/ADRD) research. The SPPB has proven its value in evaluating lower extremity function and mobility in older adults, providing predictive insights into declines in daily living activities, falls, hospitalization, disability, and mortality.
Recognizing the need for accessible and automated assessment tools, this project endeavors to design a mobile app with multi-fold functionality. The final version will guide users through SPPB tests, offer real-time performance scoring, and facilitate frequent, objective, and accurate physical and cognitive assessments. This is particularly critical for monitoring the progression of ADRD, identifying subtle physical changes indicative of cognitive decline, and enabling timely interventions tailored to patients' evolving needs.
Our goal is to collect video data from 20 to 30 participants 18+ years of age who are considered healthy with no severe mobility issues to perform the SPPB. The video data will be used to develop a prototype of the SPPB application and validate testing in the lab. The video recording will be automatically encrypted and securely uploaded to Stanford privacy protected computer servers to test and refine the application results.
详细描述
In response to the growing significance of the Short Physical Performance Battery (SPPB) in Alzheimer's Disease and Related Dementias (AD/ADRD) research, this project aims to create a mobile application that enhances physical and cognitive assessments. The SPPB has proven its value in evaluating lower extremity function and mobility in older adults, providing predictive insights into declines in daily living activities, falls, hospitalization, disability, and mortality. Moreover, recent research has revealed the potential of SPPB in detecting cognitive decline through gait and hand movement analysis at various stages of AD and Mild Cognitive Impairment (MCI). Recognizing the need for accessible and automated assessment tools, this project endeavors to design a mobile app with multi-fold functionality. It will guide users through SPPB tests, offer real-time performance scoring, and facilitate frequent, objective, and accurate physical and cognitive assessments. This is particularly critical for monitoring the progression of ADRD, identifying subtle physical changes indicative of cognitive decline, and enabling timely interventions tailored to patients' evolving needs.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Adult (18+)
- •proficient in English
- •consider themselves healthy
- •Ability to participate in a meeting for consenting and video data collection on Stanford campus
排除标准
- •We will exclude participant that do not consent to video data collection
- •Under the age of 18
- •limited physical mobility.
- •We have no exclusions on the basis of gender or ethnic background.
结局指标
主要结局
develop an automated analysis of the SPPB clinical tests
时间窗: 1 year
Novel Biomarker Types: In this study, we propose to leverage video data to develop an automated analysis of the SPPB clinical tests, the same way that MRI data can automatically be analyzed. This will remove the need for subjective evaluation and lead to universally acceptable disease (digital) biomarkers from the video data, helping the clinicians. The video-based biomarkers will serve as quantifiable identifiers singling out specific subtype(s). Such digital biomarkers \[9-19,21\] and especially video \[20\] are transforming the development of drugs. Video, as a rich source of data, can provide novel information yet to be explored.
large-scale data collection to continuously collect data for understanding NPS disease trajectories
时间窗: 1 year
Novel Methodologies: Processing unconstrained video data collected in clinical settings with limited data points calls for new technologies. Although we use recent video recognition technologies (including those developed by us recently), applying them to clinical data and training new machine learning models poses unique challenges requiring novel methods. In addition, implementing this on mobile phones will facilitate the platforms required for large-scale data collection to continuously collect data for understanding disease trajectories.
SPPB++ mobile phone app
时间窗: 1 year
Impact: We will implement our novel algorithms in a mobile phone app, making the tests accessible and affordable to many individuals. This will enable large-scale data collection and clinical trials. The analysis of this data will identify novel biomarkers using video-based SPPB tests. The longitudinal assessment of these tests will provide a means for tracking cognitive functioning and convergence to MCI, AD, or other dementia.
次要结局
未报告次要终点
研究者
Ehsan Adeli
Professor
Stanford University