Usability and Acceptability of Wearable Technology in the Early Detection of Dementia

Background: The Early Detection of Neurodegeneration (EDoN) is a global initiative that aims to explore the potential of wearable technologies and smartphone applications to detect preclinical dementia, with aspirations to validate a digital toolkit for clinical practice. To enhance the development of an inclusive digital toolkit, we conducted a study to assess the usability and acceptability of different digital devices in people with cognitive impairments and their carers.

Method: Recruitment was conducted across various UK networks such as Join Dementia Research. Participants received the EDoN toolkit, which includes a smartwatch (Fitbit Charge 4), EEG headband (Dreem 3) and two smartphone applications (Longevity and Mezurio). Guides were provided to support the setup process. Initial interviews were conducted approximately three days after the participant received the devices, to explore initial perspectives regarding the toolkit and experiences of the setup process. Follow-up interviews were conducted two weeks later to explore the acceptability and usability of the toolkit. NVivo was used to thematically analyse the interview transcripts. Emerging themes were discussed and refined by the research group.

Result: Sixteen semi-structured interviews were conducted with nine participants, at two-time points. Four participants had mild cognitive impairment, two had frontotemporal dementia, one had Alzheimer's and two were carers. We identified three key themes, which centred around usability, acceptability and inequity. Participants expressed the wearable devices were comfortable but individuals with physical disabilities or cognitive impairments struggled to use some devices. Participants valued the feedback the devices provided such as information on sleep and heart rate, although some information was not fully understood. Participants also shared their concerns around detecting preclinical dementia and the increased anxiety around the consequences of this such as "being put in a home". Various inequities of the toolkit were uncovered such as digital exclusion relating to a lack of access to strong WiFi connection, compatible smartphones and poor digital literacy.

Conclusion: These results are informative for the further development of user-friendly digital tools for the early detection of dementia. Further work is required to ensure a digital toolkit is inclusive and provides information that can be understood by the user.