Sensor-Based Assessment of Social Isolation and Loneliness in Older Adults: A Survey.

Social isolation (SI) and loneliness are 'invisible enemies'. They affect older people's health and quality of life and have significant impact on aged care resources. While in-person screening tools for SI and loneliness exist, staff shortages and psycho-social challenges fed by stereotypes are significant barriers to their implementation in routine care. Autonomous sensor-based approaches can be used to overcome these challenges by enabling unobtrusive and privacy-preserving assessments of SI and loneliness. This paper presents a comprehensive overview of sensor-based tools to assess social isolation and loneliness through a structured critical review of the relevant literature. The aim of this survey is to identify, categorise, and synthesise studies in which sensing technologies have been used to measure activity and behavioural markers of SI and loneliness in older adults. This survey identified a number of feasibility studies using ambient sensors for measuring SI and loneliness activity markers. Time spent out of home and time spent in different parts of the home were found to show strong associations with SI and loneliness scores derived from standard instruments. This survey found a lack of long-term, in-depth studies in this area with older populations. Specifically, research gaps on the use of wearable and smart phone sensors in this population were identified, including the need for co-design that is important for effective adoption and practical implementation of sensor-based SI and loneliness assessment in older adults.

Analysis of In-Home Movement Patterns for Depression Assessment in Older Adults - A Feasibility Study.

Depression significantly impacts the wellbeing of older Australians, posing considerable challenges to their overall quality of life. This study aimed to detect in-home movement patterns of participants that could be indicative of depressive states. Utilising data collected over a 12-month period via smart home ambient sensors, this feasibility study conducted a comparative analysis using machine learning techniques on features derived from motion sensors, sociodemographic variables, and the Geriatric Depression Scale. Three machine learning models, specifically Extreme Gradient Boost (XGBoost), Random Forest (RF), and Logistic Regression (LR), were implemented. Results showed that the performance of XGBoost was relatively higher compared to RF and LR, with an Area Under the Receiver Operating Characteristic Curve (AUROC) value of 0.67. Feature analysis indicated that bathroom and kitchen movements and the level of home care support were among the top influential features influencing depression assessment. This is consistent with clinical evidence on appetite, hygiene, and overall mobility changes during depression. These findings underscore the feasibility of leveraging in-home movement monitoring as an indicator of health risks among older adults.

Detecting Depression-related Movement Changes in Older Adults using Smart Home Motion Sensors - A Feasibility Study.

Smart home sensor data is being increasingly used to identify health risks through passive tracking of specific behaviours and activity patterns. This study explored the feasibility of using motion sensor data to track changes in daytime movement patterns within the home, and their potential association with depression in older adults. This study analysed the motion sensor data collected during a one-year smart home trial, and explored their association with Geriatric Depression Scale (GDS) scores collected at three different time points during the trial (i.e., baseline, mid-trial, and end-trial). Our results showed that movement patterns are generally reduced when older adults are in a depressed state compared to when being in a not-depressed state. In particular, the reduced movement activity in depressed states was significant (p<.05) when the participant's GDS state changed between depressed and not-depressed for the first time during the three time points of the trial when GDS was collected.Clinical relevance- Our results establish the feasibility and potential use of motion sensor data from ambient sensors in a smart home for passive and remote assessment of older adults' depression status, that is comparable to their GDS scores, through changes in their in-home day-time movement patterns. Also since reduced movement activity may be a general indicator of potential health risks, this study provides preliminary evidence for using in-home movement activity monitoring as an general indicator of health risks.

The Significance and Limitations of Sensor-based Agitation Detection in People Living with Dementia.

Agitation, a commonly observed behaviour in people living with dementia (PLwD), is frequently interpreted as a response to physiological, environmental, or emotional stress. Agitation has the potential to pose health risks to both individuals and their caregivers, and can contribute to increased caregiver burden and stress. Early detection of agitation can facilitate with timely intervention, which has the potential to prevent escalation to other challenging behaviors. Wearable and ambient sensors are frequently used to monitor physiological and behavioral conditions and the collected signals can be engaged to detect the onset of an agitation episode. This paper delves into the current sensor-based methods for detecting agitation in PLwD, and reviews the strengths and limitations of existing works. Future directions to enable real-time agitation detection to empower caregivers are also deliberated, with a focus on their potential to reduce caregiver burden by facilitating early support, assistance and interventions to timely manage agitation episodes in PLwD.

Adsorptive removal of tetracycline from aqueous solutions using magnetic Fe2O3 / activated carbon prepared from Cynometra ramiflora fruit waste.

Herein, the sustainable fabrication of magnetic iron oxide nanoadsorbent prepared with activated carbon of inedible Cynometra ramiflora fruit has been investigated. Activated carbon was obtained from phosphoric acid-treated C. ramiflora fruit, which was then utilized for the synthesis of magnetic nanocomposite (CRAC@Fe2O3). The formed nanocomposite was a porous irregular dense matrix of amorphous evenly sized spherical nanoparticles, as visualized by FESEM, and also contained carbon, oxygen, iron, and phosphorous in its elemental composition. FT-IR spectrum depicted characteristic bands attributing to Fe-O, C-OH, C-N, CC, and -OH bonds. VSM and XRD results proved that CRAC@Fe2O3 was superparamagnetic with a moderate degree of crystallinity and high saturation magnetization value (1.66 emu/g). Superior surface area, pore size, and pore volume of 766.75 m2/g, 2.11 nm, and 0.4050 cm3/g respectively were measured on BET analysis of CRAC@Fe2O3 nanocomposite, indicating their suitability for use as an adsorbent. On application of this nanocomposite for adsorption of tetracycline, maximum removal of 95.78% of 50 ppm TC at pH 4, CRAC@Fe2O3 0.4 g/L in 240 min. The adsorption of TC by CRAC@Fe2O3 was confirmed as monolayer sorption by ionic interaction (R2 = 0.9999) as it followed pseudo-second-order kinetics and Langmuir isotherm (R2 = 0.9801). CRAC@Fe2O3 showed a maximum adsorption capacity of 312.5 mg/g towards TC antibiotics indicating its potential for the treatment of antibiotic-contaminated samples. Since negative ΔGo and positive ΔHo and ΔSo values were obtained at all tested temperatures during the thermodynamic studies, the adsorption was confirmed to be endothermic, spontaneous, and feasible with an enhanced degree of randomness.

Superparamagnetic hematite spheroids synthesis, characterization, and catalytic activity.

The leaf extract of Muntingia calabura is being first reported to be used for the synthesis superparamagnetic hematite nanoparticles by following the green-chemistry approach. Field Emission - Scanning Electron Microscopic image revealed the formation of irregular nano spheroids averaging at 48.57 nm in size and characteristic of Fe and O atoms, as revealed by Energy Dispersive X-Ray spectrum. X-ray diffraction analysis results proved the crystallinity of hematite diffraction planes with crystallite sizes averaging at 30.68 nm. The lattice parameter values stayed concordant with the literature. The superparamagnetic nature was attested by the high value of saturation magnetism (2.20 emu/g) with negligible coercivity and retentivity. Fourier Transform Infrared Spectroscopy results affirmed numerous moieties involved in the synthesis of hematite nanoparticles and the existence of signature Fe-O bands. Thermogravimetric analysis studies portrayed the thermal behavior nanoparticles with 28% weight loss and thermal stability was attained after 700 °C. X-ray photoelectron spectroscopy analysis confirmed the valence states of Fe and O in the hematite nanoparticles and ascertained the purity. The mesoscopic structure was revealed by Brunauer-Emmett-Teller studies with considerable surface area (112.50 m2/g). The Fenton-like catalysis mediated by the nanoparticle sample was demonstrated by degrading methylene blue dye. The remarkable degradation efficiency of 93.44% was obtained and the kinetics was conformed to a second-order model with a high R2 value. Therefore, the highly crystalline and mesoporous superparamagnetic hematite spheroids prepared using the leaf extract of M. calabura would find promising applications in various catalysis processes.

VibroSleeve: A wearable vibro-tactile feedback device for arm guidance.

Vibro-tactile feedback offers a complementary augmentation cue for motor guidance and training. Motivated by the needs of prosthetic vision rehabilitation, we explore the use of the cylindrical forearm surface to deliver arm guidance cues via vibro-tactile stimulation. We present 'VibroSleeve', a novel wearable arm motion guidance aid made up of 4x4 arrangement of vibration coin motors embedded within an elastic sleeve for delivering vibro-tactile patterns to the forearm. In this paper, we present the concept and design of VibroSleeve, along with results of preliminary evaluation. We outline key insights gained into the perceptual aspects of calibration and usable intensity bandwidth critical for reliable interpretation of encoded information. Our results demonstrate feasibility of the approach, and provide foundations for future work on developing the sleeve as a rehabilitation aid for guiding the arm towards visually perceived targets.

Elucidating the role of microstructural modification on stress corrosion cracking of biodegradable Mg4Zn alloy in simulated body fluid.

This paper investigates the effect of microstructure modification by heat treatment on stress corrosion cracking (SCC) behavior of Mg4Zn alloy in simulated body fluid (SBF). Mg4Zn alloy in as cast, solution heat treated and peak aged conditions was susceptible to SCC in SBF when strained at 3.6 × 10-6 s-1. SCC index based on fracture energy is least for solutionized alloy (0.84), while 0.88 for as cast and peak aged alloys. Fractographic analysis indicates predominantly intergranular SCC for solution treated alloy initiated by anodic dissolution near grain boundaries. As cast and peak aged alloy shows mainly transgranular failure due to hydrogen embrittlement adjacent to secondary phase particles.

Consumer Wearable Information and Health Self Management by Older Adults.

BACKGROUND: The present study was undertaken to build an evidence base focusing on an ageing population who are using or have used consumer wearables to collect and manage information about their personal health status. The primary objective was to understand the health self-management requirements, frailty and age related changes, and the health information support provided by consumer wearable devices, specifically in the context of older adults living independently. METHOD: The study aimed to recruit older adults to respond to an online questionnaire. Inclusion criteria for the selection of study participants were: Aged 55 or over, independent living, and currently using or having used a wearable device or devices for health self-management in the past year. The online survey questionnaire represented a cross-section of variables in three sections: (1) Use of wearables for health monitoring, (2) Demographics and (3) Health, physical condition and wellness. A subset of the questions was drawn from the Tilburg Frailty Indicator. RESULTS: Summary findings from the completed questionnaires suggest the use of wearable health information supports aspects of health self-management activities among independent living seniors. Personal variations and user characteristics in the extent and consistency of the use of wearable information, and user experience in the process, was more difficult to extrapolate, for example, in health information sharing. CONCLUSION: Responses to the survey do not indicate widespread use of information from consumer wearables for health self-management among older adults. However, among the respondents, more than half were willing to participate in a follow-up interview by a researcher on their wearable health information use. Further research will explore what they have to say about this information use in relation to frailty and age related changes, and about the way that such information may be integrated into health and aged care support systems.