Preliminary study on activity monitoring using an android smart-watch

The global trend for increasing life expectancy is resulting in aging populations in a number of countries. This brings to bear a pressure to provide effective care for the older population with increasing constraints on available resources. Providing care for and maintaining the independence of an older person in their own home is one way that this problem can be addressed. The EU Funded Unobtrusive Smart Environments for Independent Living (USEFIL) project is an assistive technology tool being developed to enhance independent living. As part of USEFIL, a wrist wearable unit (WWU) is being developed to monitor the physical activity (PA) of the user and integrate with the USEFIL system. The WWU is a novel application of an existing technology to the assisted living problem domain. It combines existing technologies and new algorithms to extract PA parameters for activity monitoring. The parameters that are extracted include: activity level, step count and worn state. The WWU, the algorithms that have been developed and a preliminary validation are presented. The results show that activity level can be successfully extracted, that worn state can be correctly identified and that step counts in walking data can be estimated within 3% error, using the controlled dataset

Instrumentation of a cane to detect and prevent falls

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)The number of falls is growing as the main cause of injuries and deaths in the geriatric community. As a result, the cost of treating the injuries associated with falls is also increasing. Thus, the development of fall-related strategies with the capability of real-time monitoring without user restriction is imperative. Due to their advantages, daily life accessories can be a solution to embed fall-related systems, and canes are no exception. Moreover, gait assessment might be capable of enhancing the capability of cane usage for older cane users. Therefore, reducing, even more, the possibility of possible falls amongst them. Summing up, it is crucial the development of strategies that recognize states of fall, the step before a fall (pre-fall step) and the different cane events continuously throughout a stride. This thesis aims to develop strategies capable of identifying these situations based on a cane system that collects both inertial and force information, the Assistive Smart Cane (ASCane). The strategy regarding the detection of falls consisted of testing the data acquired with the ASCane with three different fixed multi-threshold fall detection algorithms, one dynamic multi-threshold and machine learning methods from the literature. They were tested and modified to account the use of a cane. The best performance resulted in a sensitivity and specificity of 96.90% and 98.98%, respectively. For the detection of the different cane events in controlled and real-life situations, a state-of-the-art finite-state-machine gait event detector was modified to account the use of a cane and benchmarked against a ground truth system. Moreover, a machine learning study was completed involving eight feature selection methods and nine different machine learning classifiers. Results have shown that the accuracy of the classifiers was quite acceptable and presented the best results with 98.32% of overall accuracy for controlled situations and 94.82% in daily-life situations. Regarding pre-fall step detection, the same machine learning approach was accomplished. The models were very accurate (Accuracy = 98.15%) and with the implementation of an online post-processing filter, all the false positive detections were eliminated, and a fall was able to be detected 1.019s before the end of the corresponding pre-fall step and 2.009s before impact.O número de quedas tornou-se uma das principais causas de lesões e mortes na comunidade geriátrica. Como resultado, o custo do tratamento das lesões também aumenta. Portanto, é necessário o desenvolvimento de estratégias relacionadas com quedas e que exibam capacidade de monitorização em tempo real sem colocar restrições ao usuário. Devido às suas vantagens, os acessórios do dia-a-dia podem ser uma solução para incorporar sistemas relacionados com quedas, sendo que as bengalas não são exceção. Além disso, a avaliação da marcha pode ser capaz de aprimorar a capacidade de uso de uma bengala para usuários mais idosos. Desta forma, é crucial o desenvolvimento de estratégias que reconheçam estados de queda, do passo anterior a uma queda e dos diferentes eventos da marcha de uma bengala. Esta dissertação tem como objetivo desenvolver estratégias capazes de identificar as situações anteriormente descritas com base num sistema incorporado numa bengala que coleta informações inerciais e de força, a Assistive Smart Cane (ASCane). A estratégia referente à deteção de quedas consistiu em testar os dados adquiridos através da ASCane com três algoritmos de deteção de quedas (baseados em thresholds fixos), com um algoritmo de thresholds dinâmicos e diferentes classificadores de machine learning encontrados na literatura. Estes métodos foram testados e modificados para dar conta do uso de informação adquirida através de uma bengala. O melhor desempenho alcançado em termos de sensibilidade e especificidade foi de 96,90% e 98,98%, respetivamente. Relativamente à deteção dos diferentes eventos da ASCane em situações controladas e da vida real, um detetor de eventos da marcha foi e comparado com um sistema de ground truth. Além disso, foi também realizado um estudo de machine learning envolvendo oito métodos de seleção de features e nove classificadores diferentes de machine learning. Os resultados mostraram que a precisão dos classificadores foi bastante aceitável e apresentou, como melhores resultados, 98,32% de precisão para situações controladas e 94.82% para situações do dia-a-dia. No que concerne à deteção de passos pré-queda, a mesma abordagem de machine learning foi realizada. Os modelos foram precisos (precisão = 98,15%) e com a implementação de um filtro de pós-processamento, todas as deteções de falsos positivos foram eliminadas e uma queda foi passível de ser detetada 1,019s antes do final do respetivo passo de pré-queda e 2.009s antes do impacto

The use of mHealth solutions in active and healthy ageing promotion: an explorative scoping review

The global population aged 60 years and over is expected to almost double between 2015 and 2050 from 12.0% to 22.0%, which will directly impact countries' labor market composition and increase the economic pressure on their healthcare systems. One way to address these challenges is to promote Active and Healthy Ageing (AHA) using mobile Health (mHealth). This research aims to provide an initial overview of the width and the depth of contemporary preventive mHealth solutions that promote AHA among healthy, independent older adults (individuals aged 60 years and over). To do so, an explorative scoping review was applied to search online databases for recent studies (March 2015 - March 2020) addressing the promotion of mHealth solutions targeting healthy and independent older adults. We identified 31 publications that met the inclusion criteria. Most of them utilized either mobile (n=25) and/or wearable (n=11) devices. mHealth solutions mostly promoted AHA by targeting older adults’ active lifestyles or independence. Most of the studies (n=27) did not apply a theoretical framework on which the mHealth promotion was based. User-experience was positive (n=12) when the solution was easy to use but negative (n=11) when the participants were resistant or faced challenges using the device and/or technology. The review concludes that mHealth offers the opportunity to combat the issues faced by an unhealthy and dependent aging population by promoting AHA through focusing on older adults’ Lifestyle, Daily functioning, and Participation. Future research should use multidisciplinary integrated approaches and strong theoretical and methodological foundations to investigate mHealth solutions' impact on AHA behavioral change

Assistive technology to monitor activity, health and wellbeing in old age : The wrist wearable unit in the USEFIL project

This paper presents the assistive technology used to perform activity monitoring in the USEFIL (Unobtrusive Smart Environments for Independent Living) project, particularly the wrist wearable unit. USEFIL includes a number of activity monitoring devices alongside some condition specific medical devices, a dedicated electronic health record database and communication backend. The system is designed as an assistive technology to provide long-term monitoring for older people in their own home and communicate the data that is gathered into a decision support system that can be used by the older person's carers to improve their care and allow them to remain independent in their own home. The wrist wearable device developed for the USEFIL project, the various health indicators extracted from its inbuilt sensors and how these are used to understand the health and wellbeing of the older person are discussed in this paper

Design of a Wearable Balance Control Indicator

Each year, one in three elderly fall. Studies show that many factors contribute to an elderly person\u27s risk of falling, but if the factors causing imbalance are improved, a person\u27s risk of falling may be reduced. A device that detects and alerts the user of an off-balance situation before the fall occurs could identify a specific need for improved balance control. This MQP describes the design, testing, and verification of a prototype wearable device that is worn on the right hip during the sit-to-stand activity (STS) to detect and notify the user of an unbalanced STS. By signaling an off-balance situation during STS, our device notifies the user of poor balance control and identifies the need for balance control improvement

Assessment of Physical Activity in Adults with Progressive Muscle Disease

Introduction: Insufficient physical activity is a major threat to global health. Physical activity benefits peoples’ physical and mental health. The general population, including people living with disabilities and muscle wasting conditions, are recommended to avoid excessive sedentary time and engage in daily activity. Adults with progressive muscle disease experience barriers to physical activity participation, including muscle weakness, fatigue, physical deconditioning, impairment, activity limitations and participation restrictions (including societal and environmental factors), and fear of symptom exacerbation. More research is required to understand the inter-relationship between health and physical activity for adults with progressive muscle disease, particularly non-ambulant people who are under-represented in the existing research literature. Accurate measurement of FITT (frequency, intensity, time, and type of physical activity) is vital for high-quality physical activity assessment. The aim of this thesis was to assess the physical activity of ambulant and non-ambulant adults with progressive muscle disease.Systematic review findings identified various measures used to assess physical activity in adults with muscular dystrophy, including accelerometers, direct observation, heart rate monitors, calorimetry, positioning systems, activity diaries, single scales, interviews and questionnaires. None of the measures identified in the systematic review had well established measurement properties for adults with muscular dystrophy.Patient and public involvement interviews highlighted the importance of inclusive, remote, and technology-facilitated research design, the potential intrusion of direct observations of physical activity, the familiarity of questionnaires for data collection, and practical considerations to ensure wearing an activity monitor was not too burdensome.A feasibility study using multiple methods in 20 ambulant and non-ambulant adults with progressive muscle disease revealed satisfactory acceptability, interpretability, and usability of Fitbit and activity questionnaires, in both paper and electronic formats. During supervised activity tasks, Fitbit was found to have satisfactory criterion validity, reliability, and responsiveness and measurement properties were strengthened using multisensory measurement.An observational, longitudinal study that included 111 ambulant and non-ambulant adults with progressive muscle disease showed that:Activity monitoring had satisfactory validity, reliability and responsiveness using Fitbit, but there was considerable measurement error between Fitbit and the research grade GENEActiv accelerometer. Fitbit thresholds and multiple metrics (including accelerometer and heart rate data extrapolations of FITT) were appropriate for physical activity assessment in ambulant and non-ambulant adults with progressive muscle disease.Activity self-report had unsatisfactory concurrent validity, test-retest reliability, and responsiveness with substantial activity overestimation using the modified International Physical Activity Questionnaire. However, self-report properties were improved when used concurrently with Fitbit.Observed physical activity in adults with progressive muscle disease was generally low with excessive daily sedentary time. Activity frequencies, intensities and durations were lower, and activity types were more domestic, for wheelchair users and during the COVID-19 lockdown. Lower physical activity was significantly associated with greater functional impairment, less cardiorespiratory fitness, worse metabolic health, and lower quality of life. Activity optimisation thresholds and minimal clinically important differences were established.Discussion: The implications of this thesis include guidance for selection of appropriate physical activity measures by clinicians and researchers working with adults with progressive muscle disease. Fitbit is suitable in clinical practice and research for interactive, weekly remote activity monitoring or to support activity self-management and may represent an appropriate compromise between potential underestimation by accelerometry alone, and overestimation by self-report alone. A draft conceptual framework for physical activity measurement was also proposed. It includes frequency, intensity, time, and type of physical activity, and incorporates wider aspects of the physical activity construct, including somatic factors (relating to progressive muscle disease and underlying fitness) and contextual factors (relating to personal, social, and environmental situations). Future research will build on the knowledge gained in this thesis, furthering understanding of the inter-relationships between physical activity, health and wider contexts. Implementation will include testing a remote physical activity optimisation intervention that is inclusive of ambulant and non-ambulant participants, featuring Fitbit self-monitoring with a focus on optimisation of daily activity frequency and regularly interrupting sedentary time.</div

THE RELATIONSHIP BETWEEN MODIFIABLE LIFESTYLE FACTORS AND MUSCLE LIPID DEPOTS IN OLDER ADULTS

Muscle health declines with age, influencing both muscle strength and performance. Modifiable lifestyle factors may mitigate muscle dysfunction by altering muscle lipid depots. Vitamin D status, dietary intake, and physical activity each play a role in muscle health during aging. Low vitamin D status (measured as 25(OH)D) is prevalent among older adults and has been associated with functional limitations and impaired physical performance. Previously, 25(OH)D concentrations were inversely associated with extramyocellular lipid (EMCL) and our lab observed a significant positive relationship between 25(OH)D concentrations and IMCL. Studies have shown mixed results regarding the effects dietary fat intake interventions have on muscle lipid depots. It is well established that exercise contributes to improved muscle health, but to date studies have not examined the relationship between daily physical activity levels, muscle lipid depots, and local muscle tissue hemodynamics. We used novel non-invasive technology to measure gastrocnemius muscle lipid depots (Proton Magnetic Resonance Spectroscopy) and monitor local muscle tissue hemodynamics during a foot plantar flexion exercise (Near Infrared/Diffuse Correlation Spectroscopy). The first aim was to further elucidate the relationship between 25(OH)D concentrations, physical function, and muscle lipid depots. We also examined 25(OH)D concentrations and muscle lipid depots differences in older adults with varied body mass index (BMI) and physical activity levels. We observed a negative relationship between 25(OH)D concentrations and EMCL. In females, greater 25(OH)D concentrations and lower EMCL were significant predictors of faster Four Square Step Test times, independent of BMI and age. Greater EMCL and IMCL content were observed with increased BMI, but statistical significance was not reached. The second aim was to retrospectively examine the relationship between dietary fat intake and muscle lipid depots in participants enrolled in a double-blinded placebo-controlled trial. We also investigated the relationship between physical activity levels and local muscle tissue hemodynamics. Increased dietary fat intake ratio of polyunsaturated to saturated fatty acids (PUFA:SFA) and study intervention (7 days of aerobic training) were the best predictors of lower IMCL content, independent of age, BMI, and physical activity. Compared with individuals with lower physical activity levels, individuals that reported greater physical activity had lower relative blood flow and relative oxygen consumption during and after a foot plantar flexion exercise. Together these findings suggest that increased physical activity, consumption of greater PUFA:SFA, and maintenance of sufficient 25(OH)D concentrations may have favorable effects on muscle lipid depots and contribute to the preservation of muscle health

Computerised accelerometric machine learning techniques and statistical developments for human balance analysis

Balance maintenance is crucial to participating in the activities of daily life. Balance is often considered as the ability to maintain the centre of mass (COM) position within the base of support. Primarily, to maintain balance, reliance is placed on the balance related sensory systems i.e., the visual, proprioceptive and vestibular. Several factors can affect a person’s balance such as neurological diseases, ageing, medication and obesity etc. To gain insight into the balance operations, studies rely on statistical and machine learning techniques. Statistical techniques are used for inferencing while machine learning techniques proved effective for interpretation. The focus of this study was on the issues encountered in human balance analysis such as the quantification of balance by relevant features, the relationships between COM and ground projected body sway, the performance of various sensory systems in balance analysis, and their relationships between the directions of body sway (i.e., mediolateral (ML) and anteriorposterior (AP)). A portable wireless accelerometry device was developed, balance analysis methods based on the inverted pendulum were devised and evaluated for their accuracy and reliability against a setup designed to allow manual balance measurements. Balance data were collected from 23 healthy adult subjects with the mean (standard deviation) of the age, height and weight: 24.5 (4.0) years, 173.6 (6.8) cm, and 72.7 (9.9) kg respectively. The accelerometry device was attached to the subjects at the approximate position of the illac crest, while they performed 30 seconds trials of the four conditions associated with a standard balance test called the modified Clinical Test of Sensory Interaction and Balance (mCTSIB). These required standing on a hard (ground) surface with the eyes open, standing on hard surface with the eyes closed, standing on a compliant surface (sponge, 10 cm thick) with the eyes open and standing on a compliant surface with the eyes closed. Statistical and machine learning techniques such as t-test, Wilcoxon signed-rank test, the Mann-Whitney U test, Analysis of variance (ANOVA), Kruskal-Wallis test, Friedman test, correlation analysis, linear regression, Bland and Altman analysis, principal component analysis (PCA), K-means clustering, and Kohonen neural network (KNN) were employed for interpreting the measurements. The findings showed close agreement between the developed balance analysis methods and the related measurements from the manual setup for balance analysis. The COM was observed to be responsible for differing amount of sway across the subjects and could affect both the angle and ground projected sway. The AP direction was more sensitive to sway than the ML direction. The subjects were observed to depend more on their proprioceptive system to control balance. The proprioceptive system was observed to have a greater impact in controlling the AP velocity of the subjects as compared to their visual system. The proprioceptive system had no impact on the ML velocity. The visual system was responsible for the control of the ML velocity and for reducing the acceleration in both directions. It was concluded that for comparison of postural sway information, subjects with closely related COM positions should be compared, comparison should be carried out in respect to the base of their support. The sway normalisation by dividing with COM position should be performed to reduce the obscuring effect of the COM. Enhancement of the proprioceptive system should be carried out to reduce the AP velocity while enhancement of the visual system should be used to reduce the ML sway and acceleration in ML and AP directions. The velocity in the AP direction should be used to examine the performance of the proprioceptive system while the ML velocity and acceleration should be used for the visual system. The vestibular system characterised sway more in the AP direction, and hence, the AP direction should be used to examine its performance in balance