Automatic Performance Status Evaluation and Physical Activity Recognition in Cancer Patients for Medical Diagnosis Assistance

Sobresaliente (10)The evaluation of cancer patients’ recovery is still under a big grade of subjectivity from the physicians’ diagnoses. Different systems have been successfully implemented for general physical activity evaluation, nonetheless there is still a big leap of improvement into Performance Status (PS) evaluation with ECOG and Karnofsky’s Performance Status (KPS) scores. In this project an automatic system for patients’ biomonitoring based on Android technology with smartphones and wearables has been designed. As a result, objective data is provided for the oncologists’ diagnoses along with new algorithms for physical activity and PS assessment, having the latter applied to ECOG and KPS no precedent known. Furthermore, the basics for prospective implementation of gamification has been designed for boosting patients’ motivation in their recovery.La evaluación de la recuperación de pacientes con cáncer está caracterizada por un alto grado de subjetividad en los diagnósticos del personal médico. Se han implementado con éxito diferentes sistemas para la evaluación de la actividad fı́sica, sin embargo, aún existe un amplio margen de evolución dentro de la medida de la capacidad funcional con las escalas ECOG y de Karnofsky. En este proyecto se ha diseñado un sistema automático para la biomonitorización de pacientes basado en tecnologı́a Android con smartphones y wearables. Con esto se provee a los oncólogos de datos objetivos para sus diagnósticos junto con nuevos algoritmos para la evaluación de la actividad fı́sica y la capacidad funcional, estos últimos aplicados a ECOG y la escala de Karnofsky sin precedente alguno. Además, se han sentado las bases y el diseño de una futura implementación de gamificación para favorecer la motivación del paciente en su recuperación.Beca Iniciación a la Investigación de la Universidad de GranadaDepartamento de Arquitectura y Tecnología de Computadores, Universidad de Granad

Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC.

OBJECTIVES: This study is part of the ongoing development of treatment methods for metabolic syndrome (MS) project, which involves monitoring daily physical activity. In this study, we have focused on detecting walking activity from subjects which includes many other physical activities such as standing, sitting, lying, walking, running, and falling. Specially, we implemented an integrated solution for various physical activities monitoring using a mobile phone and PC. METHODS: We put the iPod touch has built in a tri-axial accelerometer on the waist of the subjects, and measured change in acceleration signal according to change in ambulatory movement and physical activities. First, we developed of programs that are aware of step counts, velocity of walking, energy consumptions, and metabolic equivalents based on iPod. Second, we have developed the activity recognition program based on PC. iPod synchronization with PC to transmit measured data using iPhoneBrowser program. Using the implemented system, we analyzed change in acceleration signal according to the change of six activity patterns. RESULTS: We compared results of the step counting algorithm with different positions. The mean accuracy across these tests was 99.6 ± 0.61%, 99.1 ± 0.87% (right waist location, right pants pocket). Moreover, six activities recognition was performed using Fuzzy c means classification algorithm recognized over 98% accuracy. In addition we developed of programs that synchronization of data between PC and iPod for long-term physical activity monitoring. CONCLUSIONS: This study will provide evidence on using mobile phone and PC for monitoring various activities in everyday life. The next step in our system will be addition of a standard value of various physical activities in everyday life such as household duties and a health guideline how to select and plan exercise considering one's physical characteristics and condition.ope

Use of Wearable Activity-Monitoring Technologies to Promote Physical Activity in Cancer Survivors: Challenges and Opportunities for Improved Cancer Care

The aim of this review was to explore the acceptability, opportunities, and challenges associated with wearable activity-monitoring technology to increase physical activity (PA) behavior in cancer survivors. A search of Medline, Embase, CINAHL, and SportDiscus was conducted from 1 January 2011 through 3 October 2022. The search was limited to English language, and peer-reviewed original research. Studies were included if they reported the use of an activity monitor in adults (+18 years) with a history of cancer with the intent to motivate PA behavior. Our search identified 1832 published articles, of which 28 met inclusion/exclusion criteria. Eighteen of these studies included post-treatment cancer survivors, eight were on active cancer treatment, and two were long-term cancer survivor studies. ActiGraph accelerometers were the primary technology used to monitor PA behaviors, with Fitbit as the most commonly utilized self-monitoring wearable technology. Overall, wearable activity monitors were found to be an acceptable and useful tool in improving self-awareness, motivating behavioral change, and increasing PA levels. Self-monitoring wearable activity devices have a positive impact on short-term PA behaviors in cancer survivors, but the increase in PA gradually attenuated through the maintenance phase. Further study is needed to evaluate and increase the sustainability of the use of wearable technologies to support PA in cancer survivors

Full-day physical activity and sedentary behaviour levels of typically developing children and adolescents in the middle east: a systematic review

Physical activity (PA) and sedentary behaviour (SB) are important components of physical behaviour associated with long-term health outcomes. Environmental and cultural factors may influence physical behaviour. To explore full day PA and SB in children and adolescents (2–18 years old) in the Middle East, a systematic literature review was performed including 183 journal articles. A wide range of PA and SB outcomes were reported, in some cases making synthesis of results difficult. As a consequence, results were generally reported narratively (MVPA time, total PA, SB time). Meta-regression of daily step count revealed females took 4600 fewer steps than males, with 3000 fewer steps on weekdays than weekends, and overweight individuals taking 2800 fewer steps/day. Steps decreased with age. Meta-regression for TV viewing time demonstrated an increase by 0.04 h per year of age. Even though environmental and cultural conditions may be different, PA and SB of children and adolescents in the Middle East were largely comparable to those of Europeans and North Americans. The wide range of data collection instruments used (both self-report questionnaire and body-worn devices) and heterogeneity of data made synthesis of reported data across studies very difficult, suggesting a need for greater standardisation of data collection methods.</p

A novel platform incorporating multiple forms of communication to support applications in a mobile environment

This thesis discusses the creation of a novel platform that incorporates multiple communication methods, including SMS, email and web-based technologies, for interacting with users of mobile communication devices. The platform utilises people in a mobile environment to solve a range of different application problems, where each problem is a separate and distinct scenario type with unique objectives. There are existing applications available that interact with users of mobile communication devices to provide a service, such as regular weather updates to the users. Other applications have been designed to manage and coordinate the users to perform tasks within a mobile environment, such as performing field studies for scientific purposes. However, the existing applications are designed for only one specific scenario, with the design and implementation solely focused on solving the objectives of that scenario. Each component of these applications needs to be developed from scratch in order to cater for the application s requirements. There is currently no integrated communications platform that offers a framework for supporting a range of different scenario types. The new platform, entitled the Connected-Mobile Platform, aims to support the rapid development and implementation of new scenarios. This platform is composed of a framework of generic components that enable the active running of multiple scenarios concurrently, with the ability to tailor to the requirements of new scenarios as they arise via a structured process. The platform facilitates a means to coordinate its users in order to tackle the objectives of a scenario. The thesis investigates several system architectures to determine an appropriate architectural design for constructing the proposed platform. The platform has a generic framework, based on a client-server architecture, to facilitate the inclusion of a multitude of scenarios. A scenario represents a problem or an event, whereby the platform can utilise and interact with users of mobile communication devices to attempt to solve the objectives of the scenario. Three mobile communication methods are supported; the Short Message Service, electronic mail and web-forms via the mobile internet. Users are able to select and switch between the different methods. The thesis describes the platform s tailored communication structure for scenarios and autonomous analysis of messages. The thesis discusses case studies of two different scenarios to evaluate the platform s facilities for rapid scenario development. The Diet Diary scenario, which is for individual users, aims to manage a user s daily calorie intake to help them reach their desired weight goal. The focus is on the platform s functionality for analysing and responding to messages autonomously. The Missing Persons scenario, which utilises multiple users, involves tracking and locating people who have been reported missing. The focus is on the platform s functionality for coordinating the multiple users, through the creation of assignments, in order to distribute the scenario objectives. The thesis concludes by highlighting the novel features of the platform and identifying opportunities for future work

Novel sedentary behaviour measurement methods: application for self-monitoring in adults

With the introduction of the technological age, increasing mechanisation has led to labour saving devices which have all-but engineered physical activity out of our lives and sedentary behaviour has now become the default behaviour during waking hours. Interventions that previously focused on improving levels of physical activity are now attempting to concurrently increase levels of physical activity and decrease time spent in sedentary behaviour. One method that has shown promise in interventions to increase physical activity and healthy eating in adults is the behaviour change technique of self-monitoring. There is now a robust set of literature indicating self-monitoring as the most promising behaviour change technique in this area. Self-monitoring is tied inherently into the recent rise in wearable technology. These new devices have the ability to track a variety of behavioural and physiological parameters and immediately make the information returnable to the user via connected mobile applications. The potential pervasive nature of these technologies and their use of robust behaviour change techniques could make them a useful tool in interventions to reduce sedentary behaviour. Therefore the overall purpose of this three study dissertation was to identify and validate technology that can self-monitor sedentary behaviour and to determine its feasibility in reducing sedentary behaviour. Study 1 Purpose: The aim of this study was to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary behaviour and/or physical activity. Methods: To identify technologies, four scientific databases were systematically searched using key terms related to behaviour, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1st, 2015. Results: The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored physical activity, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring physical activity and/or sedentary behaviour; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on physical activity (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary behaviour (activPAL VT, the LumoBack, and Darma). Conclusions: There are a large number of devices that self-monitor physical activity; however, there is a greater need for the development of tools to self-monitor sedentary time. The novelty of these devices means they have yet to be used in behaviour change interventions, although the growing field of wearable technology may facilitate this to change. Study 2 Purpose: The aim of this study was to examine the criterion and convergent validity of the LumoBack as a measure of sedentary behaviour compared to direct observation, the ActiGraph wGT3X+ and the activPAL under laboratory and free-living conditions in a sample of healthy adults. Methods: In the laboratory experiment, 34 participants wore a LumoBack, ActiGraph and activPAL monitor and were put through seven different sitting conditions. In the free-living experiment, a sub-sample of 12 participants wore the LumoBack, ActiGraph and activPAL monitor for seven days. Validity were assessed using Bland-Altman plots, mean absolute percentage error (MAPE), and intraclass correlation coefficient (ICC). T-test and Repeated Measures Analysis of Variance were also used to determine any significant difference in measured behaviours. Results: In the laboratory setting, the LumoBack had a mean bias of 76.2, 72.1 and -92.3 seconds when compared to direct observation, ActiGraph and activPAL, respectively, whilst MAPE was less than 4%. Furthermore, the ICC was 0.82 compared to the ActiGraph and 0.73 compared to the activPAL. In the free-living experiment, mean bias was -4.64, 8.90 and 2.34 seconds when compared to the activPAL for sedentary behaviour, standing time and stepping time respectively. Mean bias was -38.44 minutes when compared to the ActiGraph for sedentary time. MAPE for all behaviours were 0.75. Conclusion: The LumoBack has acceptable validity and reliability as a measure of sedentary behaviour. Study 3 Purpose: The aim of this study was to explore the use of the LumoBack as a behaviour change tool to reduce sedentary behaviour in adults. Methods: Forty-two participants (≥25 years) who had an iPhone 4S or later model wore the LumoBack without any feedback for one week for baseline measures of behaviour. Participants then wore the LumoBack for a further five weeks whilst receiving feedback on sedentary behaviour via a sedentary vibration from the device and feedback on the mobile application. Sedentary behaviour, standing time, and stepping time were objectively assessed using the LumoBack. Differences in behaviour were determined between baseline, week 1 and week 5. Participant engagement with the LumoBack was determined using Mobile app analytics software. Results: There were no statistically significant differences in behaviour between baseline and the LumoBack intervention period (p>0.05). Participants engaged most with the Steps card on the LumoBack app with peaks in engagement seen at week 5. Conclusion: This study indicates that using the LumoBack on its own was not effective in reducing sedentary behaviour in adults. Self-monitoring and feedback may need to be combined with other behaviour change strategies such as environmental restructuring to be effective. General Conclusion This thesis found that there are currently an abundance of technologies which self-monitors physical activity but a lack of devices which measuring sedentary behaviour. One such device, the LumoBack, has shown to have acceptable validity as a measure of sedentary behaviour. Whilst the use of the LumoBack as a behaviour change tool did not elicit any significant changes, its ability to be a pervasive behavioural intervention and the use of user-defined nudging can make the LumoBack, and other similar low cost, valid objective sedentary behaviour self-monitors key components in multi-faceted interventions

Validation of a method for the estimation of energy expenditure during physical activity using a mobile device accelerometer

The main goal of this paper consists on the adaption and validation of a method for the measurement of the energy expenditure during physical activities. Sensors available in a mobile device, e.g., a smartphone, a smartwatch, or others, allow the capture of several signals, which may be used to the estimation of the energy expenditure. The adaption consists in the comparison between the units of the data acquired by a tri-axial accelerometer and a mobile device accelerometer. The tests were performed by healthy people with ages between 12 and 50 years old that performed several activities, such as standing, gym (walking), climbing stairs, walking, jumping, running, playing tennis, and squatting, with a mobile device on the waist. The validation of the method showed that the energy expenditure is underestimated and super estimated in some cases, but with reliable results. The creation of a validated method for the measurement of energy expenditure during physical activities capable for the implementation in a mobile application is an important issue for increase the acceptance of the mobile applications in the market. As verified the results obtained are around 124.6 kcal/h, for walking activity, and 149.7 kcal/h, for running activity.This work was supported by FCT project PEst-OE/EEI/L A0008/2013 (Este trabalho foi suportado pelo projecto FCT PEst-OE/EEI/LA0008/2013). The authors would also like to acknowledge the contribution of the COST Action IC1303 – AAPELE – Architectures, Algorithms and Protocols for Enhanced Living Environments