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Methods Inf Med 2017; 56(01): 55-62
DOI: 10.3414/ME15-02-0012
Wearable Therapy
Schattauer GmbH

Detecting Anxiety States when Caring for People with Dementia

Darién Miranda
1   Computer Science Department, CICESE, Ensenada, Mexico
,
Jesús Favela
1   Computer Science Department, CICESE, Ensenada, Mexico
,
Bert Arnrich
2   Computer Engineering Department, Bogaziçi University, Istanbul, Turkey
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received: 02. November 2015

accepted in revised form: 01. August 2016

Publikationsdatum:
22. Januar 2018 (online)

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Summary

Background: Caregiving is a complex, stressful activity, which frequently leads to anxiety and the development of depressive disorders. Recent advances in wearable sensing allows to monitor relevant physiological data of the caregiver for detecting anxiety spans and for enacting coping strategies to reduce their anxiety when needed.

Objectives: This work proposes a method to infer anxiety states of caregivers when caring for people with dementia, by using physiological data.

Methods: A model using Markov chains for detecting internal anxiety states is proposed. The model is tested with a physiological dataset gathered from a naturalistic enactment experiment with 10 participants. A visual analysis for observing anxiety states is employed. The Markov chain model is evaluated by using Inter-beat Interval (IBI) data to detect 4 internal states: “Relaxed”, “Arousing”, “Anxiety”, and “Relaxing”.

Results: From the visual inspection of interbeat interval data, self-report and observation labels a total of 823 state segments were identified which contained the following states: 137 “relaxed”, 91 “arousing”, 410 “anxious”, and 185 “relaxing”. By using the average IBI value of 60 seconds segments as classification feature, the model was evaluated with a “leave one-out” cross validation with an average accuracy of 73.03%.

Conclusions: We proposed a Markov chain model for internal anxiety state detection of caregivers that care for people with dementia. The model was evaluated in a naturalistic enactment experiment with 10 participants. The resulting accuracy is comparable to previous results on stress classification.

Keywords

Anxiety - physiological stress - caregivers - dementia
 

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