Remote monitoring and AI for detecting tardive dyskinesia and improving patient outcomes
A. Sterns, L. Larsen, B. Grimm, O. S. Muir
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AbstractTardive dyskinesia (TDD) is a common debilitating side effect of antipsychotic use and risk increases with age. Characterized most notably by involuntary facial movements such as grimacing, involuntary lip, mouth, and tongue movements, and eye blinking, TDD is difficult to treat and potentially irreversible. Psychiatrists and other mental health professionals are acutely aware of the impairment and disability experienced by patients who develop TDD. Early detection of TDD is critical so that appropriate interventions can be instituted. It is difficult for the most qualified diagnosticians to devote in-person time at the 4-6 times per year frequency necessary to provide every patient the 1) “active monitoring,” 2) discussion of results, 3) changes to medication and instructions expected with the urgent demands on every mental health professional today. This is increasingly challenging with the increase in telemedicine and patient populations and decreasing human resources due to the pandemic. Unfortunately, despite professionals’ best efforts, it is often too late in the process and the involuntary movements are permanent. A method for automatic TDD detection and accurate medication adherence would enable timely intervention and avoid patient stigma, lower quality of life, and expensive ongoing treatment for permanent TDD into late life.Keywords: mental health, artificial intelligence, medication adherence, tardive dyskinesia, remote patient monitoring
A. Sterns, L. Larsen, B. Grimm, O. S. Muir (2022). Remote monitoring and AI for detecting tardive dyskinesia and improving patient outcomes. Gerontechnology, 21(s),1-1
https://doi.org/10.4017/gt.2022.21.s.706.opp3