https://www.hsbi.de/publikationsserver
2000-01-01T00:00+00:001monthlyTextile-Based Sensors for Biosignal Detection and Monitoring
https://www.hsbi.de/publikationsserver/record/1592
Blachowicz, TomaszEhrmann, GuidoEhrmann, Andrea2021 Biosignals often have to be detected in sports or for medical reasons. Typical biosignals are pulse and ECG (electrocardiogram), breathing, blood pressure, skin temperature, oxygen saturation, bioimpedance, etc. Typically, scientists attempt to measure these biosignals noninvasively, i.e., with electrodes or other sensors, detecting electric signals, measuring optical or chemical information. While short-time measurements or monitoring of patients in a hospital can be performed by systems based on common rigid electrodes, usually containing a large amount of wiring, long-term measurements on mobile patients or athletes necessitate other equipment. Here, textile-based sensors and textile-integrated data connections are preferred to avoid skin irritations and other unnecessary limitations of the monitored person. In this review, we give an overview of recent progress in textile-based electrodes for electrical measurements and new developments in textile-based chemical and other sensors for detection and monitoring of biosignals.
https://www.hsbi.de/publikationsserver/record/1592engMDPI AGinfo:eu-repo/semantics/altIdentifier/doi/10.3390/s21186042info:eu-repo/semantics/altIdentifier/issn/1424-8220info:eu-repo/semantics/openAccessBlachowicz T, Ehrmann G, Ehrmann A. Textile-Based Sensors for Biosignal Detection and Monitoring. <i>Sensors</i>. 2021;21(18). doi:<a href="https://doi.org/10.3390/s21186042">10.3390/s21186042</a>ECGEMGsweathealth conditionhealth statuselderlyfirefighterssportsmanTextile-Based Sensors for Biosignal Detection and Monitoringinfo:eu-repo/semantics/articledoc-type:articletexthttp://purl.org/coar/resource_type/c_6501Acceptance of medical AI in skin cancer screening: A Choice-based Conjoint Survey
https://www.hsbi.de/publikationsserver/record/4334
Jagemann, IngaWensing, OleStegemann, ManuelHirschfeld, Gerrit2023<p><strong>Background</strong>: There is a great interest in using artificial intelligence (AI) to screen for skin cancer. This is fueled by a rising incidence of skin cancer and an increasing scarcity of trained dermatologists. AI systems, capable of identifying melanoma, could save lives, enable immediate access to screenings, reduce unnecessary care and healthcare costs. While such AI-based systems are useful from a public health perspective, past research has shown that individual patients are very hesitant about being examined by an AI system. <strong>Objective</strong>: The aim of the present study was twofold. First, to determine how important the attributes provider (in-person physician, physician via teledermatology, AI, vs. personalized AI), costs of screening (free, 10€, 25€, vs. 40€) and waiting time (immediate, 1 day, 1 week, 4 weeks) were for patients’ choices of a particular mode of skin cancer screening. Second, to investigate whether sociodemographic characteristics, especially, age, were systematically related to participants’ individual choices. <strong>Methods</strong>: The study used choice-based conjoint-analysis to examine the acceptance of medical AI for a skin cancer screening from the patient's perspective. Participants responded to twelve choice sets, each containing three screening-variants, where each variant was described through attributes; provider, costs and waiting time. Furthermore, sociodemographic characteristics (age, gender, income, job status, educational background) were assessed. <strong>Results</strong>: 126 (33%) respondents completed the online survey. The results from the conjoint analysis showed that the three attributes were more or less equal important for the participant’s choices, with provider being the most important. Inspecting the individual part worths showed that treatment by a physician was most preferred, followed by e-consultation with a physician and personalized AI. The three AI levels scored significantly lower. Concerning the relationship between sociodemographic characteristics and relative importances we found, that only age showed a significant positive association to the important of the attribute provider (r = 0.21; p < .02). Younger participants put a lesser importance on the provider than older participants. All other correlations were not significant. <strong>Conclusions</strong>: The present study adds to the growing body of research using choice-experiments to investigate the acceptance of artificial intelligence in health contexts. Future studies need to explore the reasons <em>why</em> AI is accepted or rejected and whether sociodemographic characteristics are associated this decision.</p>
<p> </p>https://www.hsbi.de/publikationsserver/record/4334engHochschule Bielefeldinfo:eu-repo/semantics/altIdentifier/doi/10.5281/zenodo.8227363info:eu-repo/semantics/openAccessJagemann I, Wensing O, Stegemann M, Hirschfeld G. <i>Acceptance of Medical AI in Skin Cancer Screening: A Choice-Based Conjoint Survey</i>. Hochschule Bielefeld; 2023. doi:<a href="https://doi.org/10.5281/zenodo.8227363">10.5281/zenodo.8227363</a>artificial intelligenceskin cancer screeningchoice experimentmelanomaconjoint analysistechnology acceptanceAcceptance of medical AI in skin cancer screening: A Choice-based Conjoint Surveyinfo:eu-repo/semantics/workingPaperdoc-type:workingPapertexthttp://purl.org/coar/resource_type/c_8042