Development of an automated speech recognition interface for personal emergency response systems
Open accessAbstract
Background: Demands on long-term-care facilities are predicted to increase at an unprecedented rate as the baby boomer generation reaches retirement age. Aging-in-place (i.e. aging at home) is the desire of most seniors and is also a good option to reduce the burden on an over-stretched long-term-care system. Personal Emergency Response Systems (PERSs) help enable older adults to age-in-place by providing them with immediate access to emergency assistance. Traditionally they operate with push-button activators that connect the occupant via speaker-phone to a live emergency call-centre operator. If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency. Additionally, a false alarm or failure to check-in at a regular interval will trigger a connection to a live operator, which can be unwanted and intrusive to the occupant. This paper describes the development and testing of an automated, hands-free, dialogue-based PERS prototype. Methods: The prototype system was built using a ceiling mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modelled after an existing call-centre protocol. Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions. Dialogue testing was completed with four adults. Results and discussion: The microphone array demonstrated improvement over the single microphone. In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting. Further testing is required with elderly voices and under different noise conditions to ensure the appropriateness of the technology. Future developments include integration of the system with an emergency detection method as well as communication enhancement using features such as barge-in capability. Conclusion: The use of an automated dialog-based PERS has the potential to provide users with more autonomy in decisions regarding their own health and more privacy in their own home.
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In-home studies are typically run with fewer participants.
“Furthermore, In home studies are typically run with fewer participants.”
From Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House (2019) · cites this paper as Hamill et al., 2009
The Methods section reports a prototype test with four participants, supporting the point that this study used a small sample. But the paper does not say that in-home studies typically have fewer participants; its Discussion calls for larger groups and testing in real-world settings. No page numbers are available in our copy. (LLM, conf=0.82)
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Research works printed but not linked: 25
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Cited by
Sorted by citations
Portet, F., Vacher, M., Golanski, C., Roux, C., & Meillon, B. (2013) · Personal and Ubiquitous Computing · doi:10.1007/s00779-011-0470-5 · Cited by 421 · see citing works
Young, V., & Mihailidis, A. (2010) · Assistive Technology · doi:10.1080/10400435.2010.483646 · Cited by 149 · see citing works
Self-citationVacher, M., Caffiau, S., Portet, F., Meillon, B., Roux, C., Elias, E., Lecouteux, B., & Chahuara, P. (2015) · ACM Transactions on Accessible Computing · doi:10.1145/2738047 · Cited by 73 · see citing works
Advances in Personal Emergency Response and Detection Systems
Hessels, V., Le Prell, G. S., & Mann, W. C. (2011) · Assistive Technology · doi:10.1080/10400435.2011.588989 · Cited by 22 · see citing works
Vacher, M., Aman, F., Rossato, S., Portet, F., & Lecouteux, B. (2019) · ACM Transactions on Accessible Computing · doi:10.1145/3310132 · Cited by 10 · see citing works
Young, V., Rochon, E., & Mihailidis, A. (2016) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-016-0207-9 · Cited by 9 · see citing works
Self-citation
- Authors
- Hamill, M., Young, V., Boger, J., & Mihailidis, A.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Mihailidis, Alex
- Venue
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2009-07-08
- Volume
- 6
- Issue
- 1
- Pages
- 26-26
- ISSN
- 1743-0003 (ISSN-L)
- PMC
- PMC2713250
- OpenAlex
- W2052793700
- Cited by
- 74
- References
- 0
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 3 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 4 · 2018: 4 · 2017: 5 · 2016: 3 · 2015: 9 · 2014: 6 · 2013: 10 · 2012: 8
- FWCI
- 7.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of NeuroEngineering and Rehabilitation (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- TSpace (University of Toronto) (submittedVersion, cc-by)
- TSpace (University of Toronto) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Social Sciences › Demography › Technology Use by Older Adults
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- personal emergency response systems, speech recognition, aging in place, older adults, microphone array, fall detection, emergency relief, long-term care, privacy, noise robustness
- MeSH terms
- Adult, Electronic Data Processing, Emergency Medical Service Communication Systems, Equipment Design, Female, Humans, Male, Noise, Speech, User-Computer Interface, Speech Recognition Software, Young Adult
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