---
_id: '7159'
abstract:
- lang: eng
text: "Background: Smart home technology powered by AI can detect anomalies and
make emergency calls, enabling residents to live safely and independently. However,
the adoption of such technologies for medical emergency detection remains limited.\r\n\r\nObjective:
This study aimed to explore consumer preferences for AI-based smart home technology
for medical emergency detection and identify predictors such as sociodemographic
variables, AI literacy, and technology affinity.\r\n\r\nMethod: A sample of 300
participants (172/300, 57.33% female; 128/300, 42.67% male, aged 18‐69 years)
completed a choice-based conjoint analysis (CBCA). Participants evaluated 15 choice
sets describing smart home variants based on cost, location, emergency detection
rate, type of sensor, and data processing.\r\n\r\nResults: Cost was the most important
attribute (relative importance [RI]=41%), followed by emergency detection rate
(RI=19%), data processing (RI=14%), and location (RI=14%). The type of sensor
was the least important attribute (RI=9%). The preferred configuration combined
an annual subscription of €70 (US $82), a 95% detection rate, wearable sensors,
personalized AI, and installation in both intimate and shared rooms. Notably,
68.3% (205/300) of participants showed a positive none utility, indicating that
even the optimal configuration did not overcome general reluctance to adopt such
systems. While most expected correlations between sociodemographic variables and
attribute importances were not observed, a significant correlation between self-reported
health status and emergency detection rate was found (r=.16, P=.007). Interestingly,
61% (167/270) of participants preferred AI over human involvement in data processing,
but logistic regression revealed that a significant correlation between self-reported
health status and emergency detection rate was found (OR=0.58, P=.04).\r\n\r\nConclusions:
These findings highlight the need to align smart home development with user preferences,
emphasizing cost-effectiveness. Additionally, AI literacy plays an important role
in technology adoption in the context of AI-based smart home technology. Further
research is needed to understand and address the reluctance to adopt AI for medical
emergency detection."
author:
- first_name: Inga
full_name: Jagemann, Inga
id: '252878'
last_name: Jagemann
orcid: 0000-0002-3468-3423
orcid_put_code_url: https://api.orcid.org/v2.0/0000-0002-3468-3423/work/226873432
- first_name: Justin
full_name: Baudisch, Justin
id: '247397'
last_name: Baudisch
orcid: 0000-0001-5565-0228
orcid_put_code_url: https://api.orcid.org/v2.0/0000-0001-5565-0228/work/226873433
- first_name: Thorsten
full_name: Jungeblut, Thorsten
id: '242294'
last_name: Jungeblut
orcid: 0000-0001-7425-8766
orcid_put_code_url: https://api.orcid.org/v2.0/0000-0001-7425-8766/work/226873434
- first_name: Günter W
full_name: Maier, Günter W
last_name: Maier
- first_name: Gerrit
full_name: Hirschfeld, Gerrit
id: '234690'
last_name: Hirschfeld
orcid: 0000-0003-2143-4564
orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-2143-4564/work/226873436
citation:
alphadin: 'Jagemann, Inga ; Baudisch, Justin ; Jungeblut,
Thorsten ; Maier, Günter W
; Hirschfeld, Gerrit: Consumer Preferences
for AI-Based Smart Home Medical Emergency Detection Among German Adults: Choice-Based
Conjoint Analysis. In: JMIR AI Bd. 5, JMIR Publications Inc. (2026), S. e94589–e94589'
ama: 'Jagemann I, Baudisch J, Jungeblut T, Maier GW, Hirschfeld G. Consumer Preferences
for AI-Based Smart Home Medical Emergency Detection Among German Adults: Choice-Based
Conjoint Analysis. JMIR AI. 2026;5:e94589-e94589. doi:10.2196/94589'
apa: 'Jagemann, I., Baudisch, J., Jungeblut, T., Maier, G. W., & Hirschfeld,
G. (2026). Consumer Preferences for AI-Based Smart Home Medical Emergency Detection
Among German Adults: Choice-Based Conjoint Analysis. JMIR AI, 5,
e94589–e94589. https://doi.org/10.2196/94589'
bibtex: '@article{Jagemann_Baudisch_Jungeblut_Maier_Hirschfeld_2026, title={Consumer
Preferences for AI-Based Smart Home Medical Emergency Detection Among German Adults:
Choice-Based Conjoint Analysis}, volume={5}, DOI={10.2196/94589},
journal={JMIR AI}, publisher={JMIR Publications Inc.}, author={Jagemann, Inga
and Baudisch, Justin and Jungeblut, Thorsten and Maier, Günter W and Hirschfeld,
Gerrit}, year={2026}, pages={e94589–e94589} }'
chicago: 'Jagemann, Inga, Justin Baudisch, Thorsten Jungeblut, Günter W Maier, and
Gerrit Hirschfeld. “Consumer Preferences for AI-Based Smart Home Medical Emergency
Detection Among German Adults: Choice-Based Conjoint Analysis.” JMIR AI
5 (2026): e94589–e94589. https://doi.org/10.2196/94589.'
ieee: 'I. Jagemann, J. Baudisch, T. Jungeblut, G. W. Maier, and G. Hirschfeld, “Consumer
Preferences for AI-Based Smart Home Medical Emergency Detection Among German Adults:
Choice-Based Conjoint Analysis,” JMIR AI, vol. 5, pp. e94589–e94589, 2026.'
mla: 'Jagemann, Inga, et al. “Consumer Preferences for AI-Based Smart Home Medical
Emergency Detection Among German Adults: Choice-Based Conjoint Analysis.” JMIR
AI, vol. 5, JMIR Publications Inc., 2026, pp. e94589–e94589, doi:10.2196/94589.'
short: I. Jagemann, J. Baudisch, T. Jungeblut, G.W. Maier, G. Hirschfeld, JMIR AI
5 (2026) e94589–e94589.
date_created: 2026-09-15T22:05:30Z
date_updated: 2026-09-16T08:20:11Z
doi: 10.2196/94589
intvolume: ' 5'
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: e94589-e94589
publication: JMIR AI
publication_identifier:
eissn:
- 2817-1705
publication_status: published
publisher: JMIR Publications Inc.
status: public
title: 'Consumer Preferences for AI-Based Smart Home Medical Emergency Detection Among
German Adults: Choice-Based Conjoint Analysis'
type: journal_article
user_id: '220548'
volume: 5
year: '2026'
...