Methodology

Development of an automated speech recognition interface for personal emergency response systems

Melinda Hamill¹ , Vicky Young² , Jennifer Boger² and Alex Mihailidis²

¹  The Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada

²  Intelligent Assistive Technology and Systems Lab, Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, ON, Canada

author email corresponding author email

Journal of NeuroEngineering and Rehabilitation 2009, 6:26doi:10.1186/1743-0003-6-26

Published:	8 July 2009

Abstract

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.