Fusion of Unobtrusive Sensing Solutions for Sprained Ankle Rehabilitation Exercises Monitoring in Home Environments

The ability to monitor Sprained Ankle Rehabilitation Exercises (SPAREs) in home environments can help therapists ascertain if exercises have been performed as prescribed. Whilst wearable devices have been shown to provide advantages such as high accuracy and precision during monitoring activities, disadvantages such as limited battery life and users’ inability to remember to charge and wear the devices are often the challenges for their usage. In addition, video cameras, which are notable for high frame rates and granularity, are not privacy-friendly. Therefore, this paper proposes the use and fusion of privacy-friendly and Unobtrusive Sensing Solutions (USSs) for data collection and processing during SPAREs in home environments. The present work aims to monitor SPAREs such as dorsiflexion, plantarflexion, inversion, and eversion using radar and thermal sensors. The main contributions of this paper include (i) privacy-friendly monitoring of SPAREs in a home environment, (ii) fusion of SPAREs data from homogeneous and heterogeneous USSs, and (iii) analysis and comparison of results from single, homogeneous, and heterogeneous USSs. Experimental results indicated the advantages of using heterogeneous USSs and data fusion. Cluster-based analysis of data gleaned from the sensors indicated an average classification accuracy of 96.9% with Neural Network, AdaBoost, and Support Vector Machine, amongst others.

Unobtrusive Sensing Technology Detects Ecologically Valid Spatiotemporal Patterns of Daily Routines Distinctive to Persons with Mild Cognitive Impairment

Background The ability to capture people’s movement throughout their home is a powerful approach to inform spatiotemporal patterns of routines associated with cognitive impairment. The study estimated indoor room activities over 24 hours and investigated relationships between diurnal activity patterns and mild cognitive impairment (MCI). Methods 161 older adults (26 with MCI) living alone (age=78.9±9.2) were included from two study cohorts–the Oregon Center for Aging & Technology and the Minority Aging Research Study. Indoor room activities were measured by the number of trips made to rooms (bathroom, bedroom, kitchen, living room). Trips made to rooms (transitions) were detected using passive infrared motion sensors fixed on the walls for a month. Latent trajectory models were used to identify distinct diurnal patterns of room activities and characteristics associated with each trajectory. Results Latent trajectory models identified two diurnal patterns of bathroom usage (high; low usage). Participants with MCI were more likely to be in the high bathroom usage group that exhibited more trips to the bathroom than the low usage group (OR=4.1,95%CI [1.3-13.5],p=0.02). For kitchen activity, two diurnal patterns were identified (high; low activity). Participants with MCI were more likely to be in the high kitchen activity group that exhibited more transitions to the kitchen throughout the day and night than the low kitchen activity group (OR=3.2,95%CI [1.1-9.1],p=0.03). Conclusions The linkage between bathroom and kitchen activities with MCI may be the result of biological, health, and environmental factors in play. In-home, real-time unobtrusive-sensing offers a novel way of delineating cognitive health with chronologically-ordered movement across indoor locations.

Fusion of Unobtrusive Sensing Solutions for Home-Based Activity Recognition and Classification Using Data Mining Models and Methods

This paper proposes the fusion of Unobtrusive Sensing Solutions (USSs) for human Activity Recognition and Classification (ARC) in home environments. It also considers the use of data mining models and methods for cluster-based analysis of datasets obtained from the USSs. The ability to recognise and classify activities performed in home environments can help monitor health parameters in vulnerable individuals. This study addresses five principal concerns in ARC: (i) users’ privacy, (ii) wearability, (iii) data acquisition in a home environment, (iv) actual recognition of activities, and (v) classification of activities from single to multiple users. Timestamp information from contact sensors mounted at strategic locations in a kitchen environment helped obtain the time, location, and activity of 10 participants during the experiments. A total of 11,980 thermal blobs gleaned from privacy-friendly USSs such as ceiling and lateral thermal sensors were fused using data mining models and methods. Experimental results demonstrated cluster-based activity recognition, classification, and fusion of the datasets with an average regression coefficient of 0.95 for tested features and clusters. In addition, a pooled Mean accuracy of 96.5% was obtained using classification-by-clustering and statistical methods for models such as Neural Network, Support Vector Machine, K-Nearest Neighbour, and Stochastic Gradient Descent on Evaluation Test.

Localisation of Room Occupants in Home Environments using Unobtrusive Sensing Solutions

This paper proposes the localisation of room occupants in home environments using Unobtrusive Sensing Solutions (USSs). The ability to localise room occupants in home environments can help in the objective monitoring of sedentary behaviour. While wearable sensors can provide tangible information on health and wellness, they have battery life issues and the inability to perform prolonged monitoring. This work uses heterogeneous USSs in the form of an Infrared Thermopile Array (ITA-64) thermal sensor and a Multi-Chirp Frequency Modulated Continuous Wave Mono-pulse (MC-FMCW-M) Radar sensor to monitor room occupants. Digital filters and background subtraction algorithms were used to process the thermal images gleaned from the ITA-64 thermal sensors. The MC-FMCW-M Radar sensor used multi-chirp and Doppler shift principles to estimate the exact location of the targeted room occupants. The estimated distances from the Radar Sensor were compared with ground truth values. Experimental results demonstrated the ability to identify thermal blobs of occupants present in the room at any particular time. Data analyses indicated no significant difference (p = 0.975) and a very strong positive correlation (r = 0.998) between the ground truth distance values and those obtained from the Radar Sensor.

Smart Band for Monitoring Vitals for Elderly People in Quarantine

Corona virus disease 2019 (COVID-19) has emerged as a pandemic with serious clinical manifestations including death. A pandemic at the large-scale like COVID-19 places extraordinary demands on the world’s health systems, dramatically devastates vulnerable populations, and critically threatens the global communities in an unprecedented way. While tremendous efforts at the frontline are placed on detecting the virus, providing treatments and developing vaccines, it is also critically important to examine the technologies and systems for tackling disease emergence, arresting its spread and especially the strategy for diseases prevention. The objective of this article is to review enabling technologies and systems with various application scenarios for handling the COVID-19 crisis. The article will focus specifically on 1) wearable devices suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals; 2) unobtrusive sensing systems for detecting the disease and for monitoring patients with relatively mild symptoms whose clinical situation could suddenly worsen in improvised hospitals; and 3) telehealth technologies for the remote monitoring and diagnosis of COVID-19 and related diseases. Finally, further challenges and opportunities for future directions of development are highlighted.

Implementation of unobtrusive sensing systems for elderly care: Scoping review (Preprint)

BACKGROUND The continuous growth of the elderly population will have implications for the organization of health and social care. Potentially, in-home monitoring unobtrusive sensing systems (USSs) can be used to support (in)formal caregivers of elderlies as they can monitor deviant physical and physiological behavior changes. Most of the existing USSs are not specific to elderly care. Hence, for facilitating the implementation of existing USSs in elderly care, it is important to know which USSs would be more suitable for elderlies. OBJECTIVE Therefore, this scoping review aims to examine the literature a) to identify current unobtrusive sensing systems (USSs) for monitoring human activities and behaviors and b) then assess them for implementation readiness for elderly care. METHODS A structured search was conducted in 'Scopus', 'Web of Science', and 'ACM digital library' databases. Predefined inclusion criteria included studies: on unobtrusive sensor-based technology; experimental in nature; aiming to monitor human social, emotional, physical, and physiological behavior; having potential to be scalable in in-home care; having at least 5 adults as participants. By using these criteria, studies were screened by title, abstract and full-text. A deductive thematic analysis based on the implementation framework of Proctor E. et al. (2011) along with additional outcome ‘external validity’ was applied to the included studies to identify the factors contributing to successful implementation. Lastly, identified factors were used to report the implementation readiness of included studies for elderly care. RESULTS 52 studies were included in the review. Deductive analysis using Proctor’s implementation framework resulted in six factors that can contribute to the successful implementation of USSs in elderly care. They are study settings, age of participants, activities monitored, sensor setup, sensing technology used, and usefulness of USSs. These factors were associated with the implementation outcomes as follows: study settings and age of participants contribute to external validity; sensor setup contributes to acceptability; usefulness of USSs contributes to adoption; activities monitored contributes to appropriateness; sensing technology used contributes to implementation cost. Further, the implementation assessment of included 52 studies showed that none of the studies has addressed all the identified factors. But this assessment was useful in highlighting studies that have addressed multiple factors, thus making such studies a step ahead in the implementation process. CONCLUSIONS This review is the first to scope the state-of-the-art USSs suitable for elderly care. Though included 52 USSs studies fulfills the basic criteria to be suitable for elderly care, but systems leveraging radio frequency technology in no contact sensor setup for monitoring life-risk or health wellness activities appear to be more fit in elderly care. Lastly, this review has extended the discussion on the term ‘unobtrusiveness’ as 'a property of systems which cannot be measured in binary as it varies a lot with user perception and context’.

Simple Wireless Impedance Pneumography System for Unobtrusive Sensing of Respiration

This extended paper presents the development and implementation at a prototype level of a wireless, low-cost system for the measurement of the electrical bioimpedance of the chest with two channels using the AD5933 in a bipolar electrode configuration to measure impedance pneumography. The measurement device works for impedance measurements ranging from 1 Ω to 1800 Ω. Fifteen volunteers were measured with the prototype. We found that the left hemithorax has higher impedance compared to the right hemithorax, and the acquired signal presents the phases of the respiratory cycle with variations between 1 Ω, in normal breathing, to 6 Ω in maximum inhalation events. The system can measure the respiratory cycle variations simultaneously in both hemithorax with a mean error of −0.18 ± 1.42 BPM (breaths per minute) in the right hemithorax and −0.52 ± 1.31 BPM for the left hemithorax, constituting a useful device for the breathing rate calculation and possible screening applications.