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1000
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Abstract/Summary
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Purpose!#!While demand for telemedicine is increasing, patients are currently restricted to tele-consultation for the most part. Fundamental diagnostics like the percussion still require the in person expertize of a physician. To meet today's challenges, a transformation of the manual percussion into a standardized, digital version, ready for telemedical execution is required.!##!Methods!#!In conjunction with a comprehensive telemedical diagnostic system, in which patients can get examined by a remote-physician, a series of three robotic end-effectors for mechanical percussion were developed. Comprising a motor, a magnetic and a pneumatic-based version, the devices strike a pleximeter to perform the percussion. Emitted sounds were captured using a microphone-equipped stethoscope. The 84 recordings were further integrated into a survey in order to classify lung and non-lung samples.!##!Results!#!The study with 21 participants comprised physicians, medical students and non-medical-related raters in equal parts. With 71.4% correctly classified samples, the ventral motorized device prevailed. While the result is significantly better compared to a manual or pneumatic percussion in this very setup, it only has a small edge over the magnetic devices. In addition, for all ventral versions non-lung regions were rather correctly identified than lung regions.!##!Conclusion!#!The overall setup proves the feasibility of a telemedical percussion. Despite the fact, that produced sounds differ compared to today's manual technique, the study shows that a standardized mechanical percussion has the potential to improve the gold standard's accuracy. While further extensive medical evaluation is yet to come, the system paves the way for future uncompromised remote examinations.
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1000
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Hinweis
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DeepGreen-ID: 96f726f42a554bd6b2cc3446e0fe70f9 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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