@article{164,
  keywords = {automated speech recognition, personal emergency response system},
  author = {Melinda Hamill and Vicky Young and Jennifer Boger and Alex Mihailidis},
  title = {Development of an automated speech recognition interface for personal emergency response systems},
  abstract = {<p><strong>Background</strong><br />
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.</p>
},
  year = {2009},
  journal = {Journal of NeuroEngineering and Rehabilitation},
  volume = {6},
  month = {07/2009},
  url = {https://jneuroengrehab.biomedcentral.com/articles/10.1186/1743-0003-6-26},
  doi = {https://doi.org/10.1186/1743-0003-6-26},
}