Extensible Sensing Platform

    Psychiatric nursing [1] involves the care of patients with mental illnesses, such as schizophrenia, dementia, depression, or bipolar disorder. Depending on the severity of their psychiatric symptoms, a part of them need to occupy inpatient beds to receive acute psychiatric treatment. Many interventions are associated with the behavior of patients and nurses are forced to deal directly with patients who are not confined to their beds. Thus, psychiatric nurses require considerable resilience and expertise in assessing and managing human behavior to maintain a delicate balance between the need to prevent and manage patients’ irregular or prohibited behavior (i.e., controlling patients’ prohibited behavior) and the need to promote the health and welfare of patients (i.e., caring patients) [2]. This research sought to reduce the demands on psychiatric nurses by developing a technological solution, i.e., an extensible sensing and feedback platform, to identify early warning signs of patients’ irregular behavior based on collected biosignals and contextual information for the management of patients with psychiatric illnesses. Through properly summarizing and presenting these early warning signs, healthcare workers can prevent and manage patients’ prohibited behavior, which promote the health and welfare of patients in the least restrictive manner

 

Discovering Nursing Difficulties through Participatory Workshops

 

    To identify the difficulties encountered by nursing staff when treating inpatients with mental disorders in acute psychiatric units, we organized two participatory workshops involving eight experts in psychiatric nursing. All of the experts, aged from 35 to 45 years, had worked as registered nurses for more than ten years at the Taipei City Psychiatric Center (TCPC) and specialized in providing inpatient psychiatric care for children, adolescents, geriatrics, and patients with substance abuse. Our aim was to explore the opportunities and constrains involved in using sensing and feedback technology, such as wearable devices, and environmental sensing devices. The moderator of the workshops was a researcher with a background in engineering. After explaining the objective of the workshops, the eight participants were divided into four groups of two to facilitate small-group discussions. To promote cross-disciplinary thinking, we also assigned to each group a researcher with a background in engineering (to outline some alternative technologies) as well as a researcher with a background in industrial and commercial design (to render design scenarios as a concrete story line). The themes identified through analysis of the data was then used in the development of our sensing and feedback system on which medical workers can flexibly prescribe required sensing and feedback modules to stack. (updated in Feb, 2017)