Societal challenges associated with caring for the physical and mental health of older adults worldwide have grown at an unprecedented pace, increasing demand for health-care services and technologies Despite the development of several assistive systems tailored to older adults, the rate of adoption of health technologies is low. This review discusses the ethical and acceptability challenges resulting in low adoption of health technologies specifically focused on smart homes for older adults. The findings have been structured in two categories: Ethical Considerations (Privacy, Social Support, and Autonomy) and Technology Aspects (User Context, Usability, and Training). The findings conclude that older adults community is more likely to adopt assistive systems when four key criteria are met. The technology should: be personalized toward their needs, protect their dignity and independence, provide user control, and not be isolating. Finally, we recommend researchers and developers working on assistive systems to: (1) provide interfaces via smart devices to control and configure the monitoring system with feedback for the user, (2) include various sensors/devices to architect a smart home solution in a way that is easy to integrate in daily life, and (3) define policies about data ownership.

Current methods of measuring heart rate (HR) and oxygen levels (SPO2) require physical contact, are individualised, and for accurate oxygen levels may also require a blood test. No-touch or non-invasive technologies are not currently commercially available for use in healthcare settings. To date, there has been no assessment of a system that measures HR and SPO2 using commercial off-the-shelf camera technology that utilises R, G, B, and IR data. Moreover, no formal remote photoplethysmography studies have been performed in real-life scenarios with participants at home with different demographic characteristics. This novel study addresses all these objectives by developing, optimising, and evaluating a system that measures the HR and SPO2 of 40 participants. HR and SPO2 are determined by measuring the frequencies from different wavelength band regions using FFT and radiometric measurements after pre-processing face regions of interest (forehead, lips, and cheeks) from colour, IR, and depth data. Detrending, interpolating, hamming, and normalising the signal with FastICA produced the lowest RMSE of 7.8 for HR with the r-correlation value of 0.85 and RMSE 2.3 for SPO2. This novel system could be used in several critical care settings, including in care homes and in hospitals and prompt clinical intervention as required.

a rapidly ageing population requires support systems which would enable them to preserve dwellers' independence without compromising on their safety or their quality of life. Smart homes for the elderly have the potential to offer unobtrusive health and wellness monitoring. The aim is to provide a safe, independent living environment which can identify and predict problems by monitoring the activities of daily living (ADLs) of the inhabitants. For this, a system able to handle continuous streams of data is required. Such a system can extract the information by using appropriate classification and learning algorithms and thus allow the remote monitoring of health and wellbeing at a high level. The implementation requires: the use of appropriate sensing technologies, identification of ADLs, data pre-processing techniques and machine learning algorithms. This is challenging due to individual differences: such a system must be able to personalize individual needs. Our contribution was the design and implementation of a platform to smartly monitor health condition of elderly using sensor data from a smart home, through an interactive user interface which is user-friendly and multiplatform. This proof-of-concept used off-line data, with the view to extend to real-time data collection in the future, which could then be used to inform support providers remotely.

Participants took part in the Automated Remote Pulse Oximetry System (ARPOS) study where their vitals including heart rate and blood oxygenation level were measured using a camera-based system. Participants were asked to stand or sit in front of a Kinect V2 camera in resting state and later also retake vitals after doing some light exercise. The study took approximately 35 to 45 minutes per participant. In order to take part in the research study, participants were required to have an XBOX One or a Windows OS computer. The anonymized data including the regions of interest extracted from the face (forehead, cheeks and lips) collected from the study are available from DOI: https://doi.org/10.5281/zenodo.6522389 (Pireh Pirzada, Automated Remote Pulse Oximetry System (ARPOS), May 2022).

Participants took part in the Automated Remote Pulse Oximetry System (ARPOS) study where their vitals including heart rate and blood oxygenation level were measured using a camera-based system. Participants were asked to stand or sit in front of a Kinect V2 camera in resting state and later also retake vitals after doing some light exercise. The study took approximately 35 to 45 minutes per participant. In order to take part in the research study, participants were required to have an XBOX One or a Windows OS computer. The anonymized data including the regions of interest extracted from the face (forehead, cheeks and lips) collected from the study are available from DOI: https://doi.org/10.5281/zenodo.6522389 (Pireh Pirzada, Automated Remote Pulse Oximetry System (ARPOS), May 2022).