A review of activity trackers for senior citizens: research perspectives, commercial landscape and the role of the insurance industry

The objective assessment of physical activity levels through wearable inertial-based motion detectors for the automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in the literature. However, their application to older adults can present particular constraints. This paper reviews the adoption of wearable devices in senior citizens by describing various researches for monitoring physical activity indicators, such as energy expenditure, posture transitions, activity classification, fall detection and prediction, gait and balance analysis, also by adopting consumer-grade fitness trackers with the associated limitations regarding acceptability. This review also describes and compares existing commercial products encompassing activity trackers tailored for older adults, thus providing a comprehensive outlook of the status of commercially available motion tracking systems. Finally, the impact of wearable devices on life and health insurance companies, with a description of the potential benefits for the industry and the wearables market, was analyzed as an example of the potential emerging market drivers for such technology in the future

Discovering user mobility and activity in smart lighting environments

"Smart lighting" environments seek to improve energy efficiency, human productivity and health by combining sensors, controls, and Internet-enabled lights with emerging “Internet-of-Things” technology. Interesting and potentially impactful applications involve adaptive lighting that responds to individual occupants' location, mobility and activity. In this dissertation, we focus on the recognition of user mobility and activity using sensing modalities and analytical techniques. This dissertation encompasses prior work using body-worn inertial sensors in one study, followed by smart-lighting inspired infrastructure sensors deployed with lights. The first approach employs wearable inertial sensors and body area networks that monitor human activities with a user's smart devices. Real-time algorithms are developed to (1) estimate angles of excess forward lean to prevent risk of falls, (2) identify functional activities, including postures, locomotion, and transitions, and (3) capture gait parameters. Two human activity datasets are collected from 10 healthy young adults and 297 elder subjects, respectively, for laboratory validation and real-world evaluation. Results show that these algorithms can identify all functional activities accurately with a sensitivity of 98.96% on the 10-subject dataset, and can detect walking activities and gait parameters consistently with high test-retest reliability (p-value < 0.001) on the 297-subject dataset. The second approach leverages pervasive "smart lighting" infrastructure to track human location and predict activities. A use case oriented design methodology is considered to guide the design of sensor operation parameters for localization performance metrics from a system perspective. Integrating a network of low-resolution time-of-flight sensors in ceiling fixtures, a recursive 3D location estimation formulation is established that links a physical indoor space to an analytical simulation framework. Based on indoor location information, a label-free clustering-based method is developed to learn user behaviors and activity patterns. Location datasets are collected when users are performing unconstrained and uninstructed activities in the smart lighting testbed under different layout configurations. Results show that the activity recognition performance measured in terms of CCR ranges from approximately 90% to 100% throughout a wide range of spatio-temporal resolutions on these location datasets, insensitive to the reconfiguration of environment layout and the presence of multiple users.2017-02-17T00:00:00

The validity of an accelerometer-based activity monitoring system and the consistency of locomotive activity of community-living older adults

BACKGROUND: The amount and intensity of people's activities are related to latent chronic diseases and the aging process. Accurate information about people's patterns of activity in their natural environments would go a long way toward understanding the relationship between types/levels of activity and health. Unlike the commercially available activity monitors, an algorithm developed at Boston University utilizes frequency (cycles/second) to identify overground gait and pedaling. These studies evaluate the validity of this system in a real-life environment and then investigate people's locomotive behavior across weekdays of the same week. METHODS: Wearing the monitoring system developed at BU on their right ankles, 16 older adults performed a battery of functional locomotive activities continuously in a residential setting, while being video recorded for reference. For the validity algorithm output regarding gait and pedaling variables was statistically compared to the video analysis of the same using the intraclass correlation coefficient (ICC). To investigate the consistency of locomotor behavior across weekdays of the same week, 227 older adults wore the monitoring system under study on their right ankles continuously for a week. Daily gait and pedaling values were correlated across weekdays of the same week also using ICCs. An investigation into the differences in gait variability for the average of 3 weekdays according to the subgroups; age, gender, and BMI was conducted on this sample using the Wilcoxon Signed Ranks test. RESULTS: Three of the four gait validity ICCs were significant (p ≤ 0.019) ranging from 0.267 to 0.778. All pedaling validity variables had ICCs ≥ 0.993 The locomotive consistency study found all 6 daily gait variables significantly (p < 0.001) correlated across 3 weekdays, ranging from 0.534 to 0.914. Three of four ICCs for pedaling consistency variables were significant (p ≤ 0.029) ranging from 0.277 to 0.838. CONCLUSIONS: This study's validity results support this monitoring system's gait and pedaling identification approach. There is also evidence to suggest how the system could improve its real-life locomotive detection validity and potentially diversify its applications. Additionally, based on this dissertation's results, some of people's daily locomotive behaviors remain relatively constant over weekdays during the same week

Randomized controlled trial of a home-based action observation intervention to improve walking in Parkinson disease

Published in final edited form as: Arch Phys Med Rehabil. 2016 May ; 97(5): 665–673. doi:10.1016/j.apmr.2015.12.029.OBJECTIVE: To examine the feasibility and efficacy of a home-based gait observation intervention for improving walking in Parkinson disease (PD). DESIGN: Participants were randomly assigned to an intervention or control condition. A baseline walking assessment, a training period at home, and a posttraining assessment were conducted. SETTING: The laboratory and participants' home and community environments. PARTICIPANTS: Nondemented individuals with PD (N=23) experiencing walking difficulty. INTERVENTION: In the gait observation (intervention) condition, participants viewed videos of healthy and parkinsonian gait. In the landscape observation (control) condition, participants viewed videos of moving water. These tasks were completed daily for 8 days. MAIN OUTCOME MEASURES: Spatiotemporal walking variables were assessed using accelerometers in the laboratory (baseline and posttraining assessments) and continuously at home during the training period. Variables included daily activity, walking speed, stride length, stride frequency, leg swing time, and gait asymmetry. Questionnaires including the 39-item Parkinson Disease Questionnaire (PDQ-39) were administered to determine self-reported change in walking, as well as feasibility. RESULTS: At posttraining assessment, only the gait observation group reported significantly improved mobility (PDQ-39). No improvements were seen in accelerometer-derived walking data. Participants found the at-home training tasks and accelerometer feasible to use. CONCLUSIONS: Participants found procedures feasible and reported improved mobility, suggesting that observational training holds promise in the rehabilitation of walking in PD. Observational training alone, however, may not be sufficient to enhance walking in PD. A more challenging and adaptive task, and the use of explicit perceptual learning and practice of actions, may be required to effect change

Life on Holidays: Study Protocol for a 3-Year Longitudinal Study Tracking Changes in Children\u27s Fitness and Fatness during the In-School Versus Summer Holiday Period

Background: Emerging evidence suggests that children become fatter and less fit over the summer holidays but get leaner and fitter during the in-school period. This could be due to differences in diet and time use between these distinct periods. Few studies have tracked diet and time use across the summer holidays. This study will measure rates of change in fatness and fitness of children, initially in Grade 4 (age 9 years) across three successive years and relate these changes to changes in diet and time use between in-school and summer holiday periods. Methods: Grade 4 Children attending Australian Government, Catholic and Independent schools in the Adelaide metropolitan area will be invited to participate, with the aim of recruiting 300 students in total. Diet will be reported by parents using the Automated Self-Administered 24-h Dietary Assessment Tool. Time use will be measured using 24-h wrist-worn accelerometry (GENEActiv) and self-reported by children using the Multimedia Activity Recall for Children and Adults (e.g. chores, reading, sport). Measurement of diet and time use will occur at the beginning (Term 1) and end (Term 4) of each school year and during the summer holiday period. Fitness (20-m shuttle run and standing broad jump) and fatness (body mass index z-score, waist circumference, %body fat) will be measured at the beginning and end of each school year. Differences in rates of change in fitness and fatness during in-school and summer holiday periods will be calculated using model parameter estimate contrasts from linear mixed effects model. Model parameter estimate contrasts will be used to calculate differences in rates of change in outcomes by socioeconomic position (SEP), sex and weight status. Differences in rates of change of outcomes will be regressed against differences between in-school and summer holiday period diet and time use, using compositional data analysis. Analyses will adjust for age, sex, SEP, parenting style, weight status, and pubertal status, where appropriate. Discussion: Findings from this project may inform new, potent avenues for intervention efforts aimed at addressing childhood fitness and fatness. Interventions focused on the home environment, or alternatively extension of the school environment may be warranted. Trial registration: Australia New Zealand Clinical Trials Registry, identifier ACTRN12618002008202. Retrospectively registered on 14 December 2018

Measuring Community Mobility in Older Adults with Parkinson’s Disease Using A Wearable GPS Sensor And Self-report Assessment Tools

Community mobility (CM) is an important instrumental activity of daily living associated with quality of life and independence. Measuring the CM of older adults, particularly those with gait disorders such as Parkinson’s disease (PD), is an important way to understand how to help people maintain mobility in the real life setting. CM is measured using self-report measures and emergent technologies, such as wearable Global Positioning System (GPS) sensors. However, the measurement properties of most available assessments have not been compared within a PD population to determine their appropriateness and identify any feasibility issues. The primary objective of this project was to compare a novel instrumented measure (Wireless Isoinertial Measurement unit with GPS; WIMU-GPS) with a self-report diary and the Life Space Assessment (LSA). To accomplish this aim, a review of literature was first conducted to show that the validity and reliability between mobility measures were seldom assessed in existing comparison studies. Then, seventy people with early to mid-stage PD (67.4 ± 6.5 years, 67.1% men) wore the WIMU-GPS and completed the self-report diaries and LSA for a 14 day period. Moderate agreements were observed between WIMuGPS and diary for trip frequency and duration (Intraclass correlation coefficient [ICC] = 0.71, 95% CI = 0.51 to 0.82; 0.67, 95% CI = 0.42 to 0.82, respectively). Disagreement between these two measures was higher for duration, particularly among individuals who regularly worked or volunteered. Convergent validity and good reliability was attained for trip frequency (Spearman correlation coefficient [rs] = 0.69, 95% CI = 0.52 to 0.81; ICC = 0.714, 95% CI = 0.51 to 0.82) and duration outside (rs = 0.43, 95% CI = 0.18 to 0.62; ICC = 0.674, 95% CI = 0.42 to 0.82) measured by the WIMU-GPS and diary. However, convergent validity was not observed between WIMU-GPS recordings and LSA reported life space size (rs = 0.39, 95% CI = 0.14 to 0.60). The LSA exhibited ceiling effects and discrimination issues. It should be avoided as a CM measure when it is feasible to use the WIMU-GPS and diary instead. The secondary objective was to determine the utility and feasibly of using WIMU-GPS to quantify different dimensions of CM in people with PD (PwP). Using a subset of participants, it was first determined that sampling error was minimized in non-discrete continuous outcomes, such as “time outside” and “area size”, when daily WIMU-GPS recordings lasted at least 600 minutes. A shorter recording minimum of at least 500 minutes per day was also suitable for discrete outcomes, such as “trip count” and “hotspot count”. The sample size precluded the determination of the optimal number of days of recording. However, data from at least seven distinct days of recording is required to capture the natural fluctuations in CM between days of the week. From a practical standpoint, a minimum of seven distinct recording days were best attained if the WIMU-GPS was worn for at least eight days. Next, the new minimum GPS recording length was adopted in a larger subset of the sample to show that PwP were regularly in the community, and they preferred vehicular travel over walking when travelling to a destination. Distances walked by PwP increased when they perceived higher levels of PD-related impact on emotional wellbeing (Pearson correlation [r] = 0.40, p \u3c 0.01) and bodily discomfort (r = 0.30, p = 0.03). Complementary diary data also showed PwP were making regular weekly visits to medical facilities. Finally, the body of work described in this Dissertation culminated in a series of practical recommendations for those interested in the CM of an older PD population or wishing to use GPS sensors for assessing real-life CM. The results of this Dissertation also are useful resources for the development of needed standards on how mobility measurements should be compared, and on the study design, data collection, and reporting of health data using GPS sensors

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

SHELDON Smart habitat for the elderly.

An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare