BACKGROUND
Globally, heart failure (HF) affects more than 64 million people and attempts to reduce its social and economic burden is a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalisations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear.
OBJECTIVE
The aim of this study was to determine the potential utility of wearable cameras to better understand activities of daily living in people living with HF.
METHODS
This study analysed wearable camera image data obtained from people living with HF. Images were processed using the E-Myscéal system with customized search terms for seven activities of daily living (physical activity, gardening, shopping, screen time, drinking, eating, and taking medication). The utility of the system for capturing specific activities was evaluated using sensitivity analysis. Daily activity image data were analysed using descriptive statistics. Differences in recorded activities were also captured for 10 participants that were readmitted to hospital for HF.
RESULTS
The E-Myscéal system demonstrated heightened sensitivity towards specific search terms. Overall, a higher number of images were recorded for eating and drinking, while the number of images for physical activity, screen time and taking medication was lower. More activities were recorded before midday compared with afternoons. Changes in the participants' daily activities were also observed before and after their hospitalization.
CONCLUSIONS
Wearable cameras can capture valuable data on daily activities of people living with HF to develop personalized interventions. A flexible interrogation system is crucial for efficient analysis of the huge volume of data produced by lifelogging devices.