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Model-Based Feature Extraction and Classification for Parkinson Disease Screening Using Gait Analysis: Development and Validation Study

Model-Based Feature Extraction and Classification for Parkinson Disease Screening Using Gait Analysis: Development and Validation Study

Only peaks that have an amplitude greater than or equal to the threshold, h, are detected and included in the output. In this study, the value for the height parameter was set to 100. An example of the graph for noise filtering with peaks is illustrated in Figure 5. This example demonstrates that the application of the Butterworth filter smooths the signal and yields an accurate step count during body turning. An example of a graph processed with a Butterworth filter, showing peaks.

Ming De Lim, Tee Connie, Michael Kah Ong Goh, Nor ‘Izzati Saedon

JMIR Aging 2025;8:e65629

Anticipated Acceptability of Blended Learning Among Lay Health Care Workers in Malawi: Qualitative Analysis Guided by the Technology Acceptance Model

Anticipated Acceptability of Blended Learning Among Lay Health Care Workers in Malawi: Qualitative Analysis Guided by the Technology Acceptance Model

Ethical clearance was provided by the University of North Carolina at Chapel Hill institutional review board (#20‐1810), the Malawi National Health Sciences Research Committee (#20/06/2566) and the Baylor College of Medicine institutional review board (H-48800). Interviewers obtained written informed consent from all participants before starting the IDIs, reminding participants that their participation was voluntary and could be withdrawn at any time.

Tiwonge E Mbeya-Munkhondya, Caroline J Meek, Mtisunge Mphande, Tapiwa A Tembo, Mike J Chitani, Milenka Jean-Baptiste, Caroline Kumbuyo, Dhrutika Vansia, Katherine R Simon, Sarah E Rutstein, Victor Mwapasa, Vivian Go, Maria H Kim, Nora E Rosenberg

JMIR Form Res 2025;9:e62741