Temple University Libraries Journals
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AnnoTS: A Multi-Activity Annotation Tool for Accelerometer Data
No full textObjective: Developing machine learning and deep learning models to detect aspects of human movement activity in naturalistic environments requires labeled datasets. AnnoTS aims to provide researchers with a software tool to annotate human movement data collected from wearable inertial measurement unit sensors. Methods: AnnoTS is a graphical user interface-based data annotation software created with Python libraries (PyQT5, PyQtGraph, and Pandas). Conclusion: AnnoTS facilitates the annotation of sensor-acquired movement data and is available as a standalone research software through an open-source code repository
Clinical Social Work in a Public Health Future
Full text linkSocial and ecological changes after the onset of the COVID-19 pandemic have surfaced the need to change how clinical interventions are administered to extend the reach and impact of interventions. The public health approach presents a framework to organize intervention efforts, and clinical social work can benefit from integrating this approach formally into its clinical education programs. This paper presents the current needs for a population-based approach to clinical service, a primer for social workers on the public health perspective. It offers critical areas to focus on integrating this public health approach into clinical social work practice
