Functional privacy concerns of older adults about pervasive health-monitoring systems

Technologies designed to support ageing can be deemed to be ageist in that they often exhibit a benevolent paternalism that tries to ‘protect’ older people. Often this involves gathering extensive data to monitor physical and cognitive decline at the expense of an individual’s privacy, with an underlying, often implicit, assumption that older adults no longer need much privacy. We consider such issues in the context of a project which seeks to promote the well-being of older adults. We conducted interviews with 20 older adults (10 males, 10 females, mean age=73) to ask, under what health and wellbeing circumstances would they wish to protect their privacy? Using thematic analysis, we uncovered six distinct reasons why older adults want to maintain privacy: protection from harm, autonomy, to present a positive social identity, to break free from social norms, to protect others, and to protect their own self-concept. We conclude that privacy is a highly valued resource for older adults and one that enables them to live fulfilling lives. We consider the design implications of our findings, noting that designers should aim to protect privacy from the outset, rather than viewing privacy as a ‘bolt-on’ that would inhibit data collection under specific circumstances. These concerns speak to the ‘paternalism’ agenda, in that older adults should be considered as active agents in the management of their own data disclosures

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

Gait Velocity Estimation using time interleaved between Consecutive Passive IR Sensor Activations

Gait velocity has been consistently shown to be an important indicator and predictor of health status, especially in older adults. It is often assessed clinically, but the assessments occur infrequently and do not allow optimal detection of key health changes when they occur. In this paper, we show that the time gap between activations of a pair of Passive Infrared (PIR) motion sensors installed in the consecutively visited room pair carry rich latent information about a person's gait velocity. We name this time gap transition time and show that despite a six second refractory period of the PIR sensors, transition time can be used to obtain an accurate representation of gait velocity. Using a Support Vector Regression (SVR) approach to model the relationship between transition time and gait velocity, we show that gait velocity can be estimated with an average error less than 2.5 cm/sec. This is demonstrated with data collected over a 5 year period from 74 older adults monitored in their own homes. This method is simple and cost effective and has advantages over competing approaches such as: obtaining 20 to 100x more gait velocity measurements per day and offering the fusion of location-specific information with time stamped gait estimates. These advantages allow stable estimates of gait parameters (maximum or average speed, variability) at shorter time scales than current approaches. This also provides a pervasive in-home method for context-aware gait velocity sensing that allows for monitoring of gait trajectories in space and time

Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

Smart homes and their users:a systematic analysis and key challenges

Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home-functional, instrumental, socio-technical; (2) users and the use of the smart home-prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home-hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns-privacy and control-that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified

An Extended TOE Framework for Cybersecurity-adoption Decisions

High-profile cybersecurity incidents, such as the 2019 Capital One data breach and the 2017 Equifax breach, have engendered doubts about firms’ trustworthiness and resulted cybersecurity becoming a critical risk factor firms must address. Breaches can precipitate extreme consequences for affected firms’ managers, shareholders, and customers. Unsurprisingly, data breaches represent IT leaders’ biggest concern. In this paper, we report on a qualitative field study in which we interviewed C-level executives and IT consultants to investigate cybersecurity concerns and factors that influence adoption decisions for cybersecurity. We found that the traditional technology-organization-environment (TOE) framework does not fully capture the range of issues in the cybersecurity context. Thus, we propose a new extended TOE framework that pertains specifically to cybersecurity-adoption decisions. This extended framework includes new dimensions, cyber catalysts, practice standards, and new factors under the traditional technology, organization, and environment dimensions

Concerns and Trade-offs in Information Technology Acceptance: The Balance between the Requirement for Privacy and the Desire for Safety

In this paper, we construct a new motivation model by bridging self-determination theory (SDT) with the unified theory of acceptance and use of technology (UTAUT). Using an explorative approach, we study how human motivational determinants influence the trade-off between safety and privacy in technology acceptance. We take the Scandinavian healthcare context as our empirical outset and explore how older Danish adults perceive sensor-based e-health monitor technology that monitors their health status. Danish municipalities have begun to use these technologies to identify early warning signs and, thereby, improve the quality of care and life by making people more self-reliant and reducing unnecessary hospitalization. However, one needs to consider ethical issues concerning privacy versus safety when implementing these technologies. After monitoring 21 respondents (mean age: 85) living independently at home over nine weeks, we interviewed them about their concerns regarding privacy and safety. We found that the respondents were willing to compromise their privacy if their autonomy and personal integrity were respected and if the benefits of sensor-based monitoring outweighed health-related threats. We used these findings and the theoretical outset to create a novel model that takes human motivation into account when using UTAUT

Ubiquitous systems and the family: Thoughts about the networked home

Developments in ubiquitous and pervasive computing herald a future in which computation is embedded into our daily lives. Such a vision raises important questions about how people, especially families, will be able to engage with and trust such systems whilst maintaining privacy and individual boundaries. To begin to address such issues, we have recently conducted a wide reaching study eliciting trust, privacy and identity concerns about pervasive computing. Over three hundred UK citizens participated in 38 focus groups. The groups were shown Videotaped Activity Scenarios [11] depicting pervasive or ubiquitous computing applications in a number of contexts including shopping. The data raises a number of important issues from a family perspective in terms of access, control, responsibility, benefit and complexity. Also findings highlight the conflict between increased functionality and the subtle social interactions that sustain family bonds. We present a Pre-Concept Evaluation Tool (PRECET) for use in design and implementation of ubicomp systems

Privacy Considerations when Designing Social Network Systems to Support Successful Ageing

A number of interventions exist to support older adults in ageing well and these typically involve support for an active and sociable ageing process. We set out to examine the privacy implications of an intervention that would monitor mobility and share lifestyle and health data with a community of trusted others. We took a privacy-by-design approach to the system in the early stages of its development, working with older adults to firstly understand their networks of trust and secondly understand their privacy concerns should information be exchanged across that network. We used a Johari Windows framework in the thematic analysis of our data, concluding that the social sharing of information in later life carried significant risk. Our participants worried about the social signaling associated with data sharing and were cautious about a system that had the potential to disrupt established networks