Closing the loop in exergaming - Health benefits of biocybernetic adaptation in senior adults

Exergames help senior players to get physically active by promoting fun and enjoyment while exercising. However, most exergames are not designed to produce recommended levels of exercise that elicit adequate physical responses for optimal training in the aged population. In this project, we developed physiological computing technologies to overcome this issue by making real-time adaptations in a custom exergame based on recommendations for targeted heart rate (HR) levels. This biocybernetic adaptation was evaluated against conventional cardiorespiratory training in a group of active senior adults through a floor-projected exergame and a smartwatch to record HR data. Results showed that the physiologically-augmented exergame leads players to exert around 40% more time in the recommended HR levels, compared to the conventional training, avoiding over exercising and maintaining good enjoyment levels. Finally, we made available our biocybernetic adaptation software tool to enable the creation of physiological adaptive videogames, permitting the replication of our study.info:eu-repo/semantics/publishedVersio

Supporting Self-Regulation of Children with ADHD Using Wearables: Tensions and Design Challenges

The design of wearable applications supporting children with Attention Deficit Hyperactivity Disorders (ADHD) requires a deep understanding not only of what is possible from a clinical standpoint but also how the children might understand and orient towards wearable technologies, such as a smartwatch. Through a series of participatory design workshops with children with ADHD and their caregivers, we identified tensions and challenges in designing wearable applications supporting the self-regulation of children with ADHD. In this paper, we describe the specific challenges of smartwatches for this population, the balance between self-regulation and co-regulation, and tensions when receiving notifications on a smartwatch in various contexts. These results indicate key considerations—from both the child and caregiver viewpoints—for designing technological interventions supporting children with ADHD

14 Years of Self-Tracking Technology for mHealth -- Literature Review: Lessons Learnt and the PAST SELF Framework

In today's connected society, many people rely on mHealth and self-tracking (ST) technology to help them adopt healthier habits with a focus on breaking their sedentary lifestyle and staying fit. However, there is scarce evidence of such technological interventions' effectiveness, and there are no standardized methods to evaluate their impact on people's physical activity (PA) and health. This work aims to help ST practitioners and researchers by empowering them with systematic guidelines and a framework for designing and evaluating technological interventions to facilitate health behavior change (HBC) and user engagement (UE), focusing on increasing PA and decreasing sedentariness. To this end, we conduct a literature review of 129 papers between 2008 and 2022, which identifies the core ST HCI design methods and their efficacy, as well as the most comprehensive list to date of UE evaluation metrics for ST. Based on the review's findings, we propose PAST SELF, a framework to guide the design and evaluation of ST technology that has potential applications in industrial and scientific settings. Finally, to facilitate researchers and practitioners, we complement this paper with an open corpus and an online, adaptive exploration tool for the PAST SELF data.Comment: 40 pages, 10 figure

A Study on Physical Exercise and General Mobility in People with Cerebral Palsy: Health through Costless Routines

[Abstract] Sedentary behavior (SB) is a common problem that may produce health issues in people with cerebral palsy (CP). When added to a progressive reduction in motor functions over time, SB can lead to higher percentages of body fat, muscle stiffness and associated health issues in this population. Regular physical activity (RPA) may prevent the loss of motor skills and reduce health risks. In this work, we analyzed data collected from 40 people (20 children and teenagers, and 20 adults) who attend two specialist centers in Seville to obtain an up-to-date picture regarding the practice of RPA in people with CP. Roughly 60% of the participants showed mostly mid/severe mobility difficulties, while 38% also had communicative issues. Most of the participants performed light-intensity physical activity (PA) at least once or twice a week and, in the majority of cases, had a neutral or positive attitude to exercising. In the Asociación Sevillana de Parálisis Cerebral (ASPACE) sample test, the higher the International Classification of Functioning, Disability and Health (ICF), the higher the percentage of negative responses to doing exercise. Conversely, in the Centro Específico de Educación Especial Mercedes Sanromá (CEEEMS), people likes PA but slightly higher ratios of positive responses were found at Gross Motor Function Classification System (GMFCS) levels V and II, agreeing with the higher personal engagement of people at those levels. We have also performed a literature review regarding RPA in CP and the use of low-cost equipment. As a conclusion, we found that RPA produces enormous benefits for health and motor functions, whatever its intensity and duration. Costless activities such as walking, running or playing sports; exercises requiring low-cost equipment such as elastic bands, certain smartwatches or video-games; or therapies with animals, among many others, have all demonstrated their suitability for such a purpose.This research was funded by the Spanish Ministry of Science and Innovation, State Plan 2017–2020: Challenges—R&D&I Projects with grant codes PID2019-104323RB-C32 and PID2019-104323RB-C33

Inaugural Research Symposium

Inaugural Research Symposium 201

Gamification applied for health promotion: does it really foster long-term engagement? A scoping review

Gamification is a popular design approach with the purpose to increase engagement and continuous use of Health Behaviour Change Support Systems (HBCSS) with the purpose to establish health and wellbeing. It is widely employed for promoting healthier life choices or for supporting people with chronic diseases in their daily activities. Yet, there is a lack of evidence concerning gamification and its ability to sustain favourable effects on health behaviour change. This paper presents a scoping review about the long-term perspective in gamified HBCSS, focusing primarily on IT-reliant systems that treat individual lifestyle habits like healthy nutrition, exercise or smoking cessation. We systematically selected studies that consider gamified HBCSS for health promotion and discuss to what extent long- term engagement is explicitly included in their design. Our results underline a deficit of consideration of the long-term perspective as well as a lack of measurement related to the lasting effects of gamification. We therefore propose to intensify the use of longitudinal and prospective observational studies in the context of HBCSS, in order to increase the level of evidence of gamification interventions

Developing an Autonomous Mobile Robotic Device for Monitoring and Assisting Older People

A progressive increase of the elderly population in the world has required technological solutions capable of improving the life prospects of people suffering from senile dementias such as Alzheimer's. Socially Assistive Robotics (SAR) in the research field of elderly care is a solution that can ensure, through observation and monitoring of behaviors, their safety and improve their physical and cognitive health. A social robot can autonomously and tirelessly monitor a person daily by providing assistive tasks such as remembering to take medication and suggesting activities to keep the assisted active both physically and cognitively. However, many projects in this area have not considered the preferences, needs, personality, and cognitive profiles of older people. Moreover, other projects have developed specific robotic applications making it difficult to reuse and adapt them on other hardware devices and for other different functional contexts. This thesis presents the development of a scalable, modular, multi-tenant robotic application and its testing in real-world environments. This work is part of the UPA4SAR project ``User-centered Profiling and Adaptation for Socially Assistive Robotics''. The UPA4SAR project aimed to develop a low-cost robotic application for faster deployment among the elderly population. The architecture of the proposed robotic system is modular, robust, and scalable due to the development of functionality in microservices with event-based communication. To improve robot acceptance the functionalities, enjoyed through microservices, adapt the robot's behaviors based on the preferences and personality of the assisted person. A key part of the assistance is the monitoring of activities that are recognized through deep neural network models proposed in this work. The final experimentation of the project carried out in the homes of elderly volunteers was performed with complete autonomy of the robotic system. Daily care plans customized to the person's needs and preferences were executed. These included notification tasks to remember when to take medication, tasks to check if basic nutrition activities were accomplished, entertainment and companionship tasks with games, videos, music for cognitive and physical stimulation of the patient

J. Silvaa , N. Hipolito b,c , P. Machadob , S. Florab , J. Cruza,b, *

Acknowledgements: This work is part of a project funded by FEDER - Fundo Europeu de Desenvolvimento Regional by COMPETE 2020 Programa Operacional Competitividade e Internacionalização (POCI) and national funds by Fundação ao para a Ciência e a Tecnologia (FCT), entitled ^ “OnTRACK project - Time to Rethink Activity Knowledge: a personalized mHealth coaching platform to tackle physical inactivity in COPD” (POCI-01-0145-FEDER-028446, PTDC/SAU-SER/28446/2017). SF and NH are being financially supported by PhD fellowships DFA/BD/6954/2020 and 2021.05188.BD, respectively, funded by FCT/MCTES, FSE, Por_Centro and UE. PM acknowledges the support provided by the FCT with the PhD fellowship. The authors acknowledge the financial support provided by FCT to their research unit Center for Innovative Care and Health Technology (UIDB/05704/2020).Pulmonology is the official journal of the Portuguese Society of Pulmonology (Sociedade Portuguesa de Pneumologia/SPP). The journal publishes 6 issues per year, mainly about respiratory system diseases in adults and clinical research. All articles published open access will be immediately and permanently free for everyone to read, download, copy and distribute.Introduction: Low physical activity (PA) levels have a negative impact on the health status of patients with Chronic Obstructive Pulmonary Disease (COPD). Smartphone applications (apps) focused on PA promotion may mitigate this problem; however, their effectiveness depends on patient adherence, which can be influenced by the technological features of the apps. This systematic review identified the technological features of smartphone apps aiming to promote PA in patients with COPD. Methods: A literature search was performed in the databases ACM Digital Library, IEEE Xplore, PubMed, Scopus and Web of Science. Papers including the description of a smartphone app for PA promotion in patients with COPD were included. Two researchers independently selected studies and scored the apps features based on a previously developed framework (38 possible features). Results: Twenty-three studies were included and 19 apps identified, with an average of 10 technological features implemented. Eight apps could be connected to wearables to collect data. The categories ‘Measuring and monitoring’ and ‘Support and Feedback’ were present in all apps. Overall, the most implemented features were ‘progress in visual format’ (n=13), ‘advice on PA’ (n=14) and ‘data in visual format’ (n=10). Only three apps included social features, and two included a web-based version of the app. Conclusions: The existing smartphone apps include a relatively small number of features to promote PA, which are mostly related to monitoring and providing feedback. Further research is warranted to explore the relationship between the presence/absence of specific features and the impact of interventions on patients’ PA levels.info:eu-repo/semantics/publishedVersio

Wearable Technology For Healthcare And Athletic Performance

Wearable technology research has led to advancements in healthcare and athletic performance. Devices range from one size fits all fitness trackers to custom fitted devices with tailored algorithms. Because these devices are comfortable, discrete, and pervasive in everyday life, custom solutions can be created to fit an individual\u27s specific needs. In this dissertation, we design wearable sensors, develop features and algorithms, and create intelligent feedback systems that promote the advancement of healthcare and athletic performance. First, we present Magneto: a body mounted electromagnet-based sensing system for joint motion analysis. Joint motion analysis facilitates research into injury prevention, rehabilitation, and activity monitoring. Sensors used in such analysis must be unobtrusive, accurate, and capable of monitoring fast-paced dynamic motions. Our system is wireless, has a high sampling rate, and is unaffected by outside magnetic noise. Magnetic noise commonly influences magnetic field readings via magnetic interference from the Earth\u27s magnetic field, the environment, and nearby ferrous objects. Magneto uses the combination of an electromagnet and magnetometer to remove environmental interference from a magnetic field reading. We evaluated this sensing method to show its performance when removing the interference in three movement dimensions, in six environments, and with six different sampling rates. Then, we localized the electromagnet with respect to the magnetic field reader, allowing us to apply Magneto in two pilot studies: measuring elbow angles and calculating shoulder positions. We calculated elbow angles to the nearest 15â—¦ with 93.8% accuracy, shoulder position in two-degrees of freedom with 96.9% accuracy, and shoulder positions in three-degrees of freedom with 75.8% accuracy. Second, we present TracKnee: a sensing knee sleeve designed and fabricated to unobtrusively measure knee angles using conductive fabric sensors. We propose three models that can be used in succession to calculate knee angles from voltage. These models take an input of voltage, calculate the resistance of our conductive fabric sensor, then calculate the change in length across the front of the knee and finally to the angle of the knee. We evaluated our models and our device by conducting a user study with six participants where we collected 240 ground truth angles and sensor data from our TracKnee device. Our results show that our model is 94.86% accurate to the nearest 15th degree angle and that our average error per angle is error per angle is 3.69 degrees. Third, we present ServesUp: a sensing shirt designed to monitor shoulder and elbow motion during the volleyball serve. In this project, we will designed and fabricated a sensing shirt that is comfortable, unobtrusive, and washable that an athlete can wear during and without impeding volleyball play. To make the shirt comfortable, we used soft and flexible conductive fabric sensors to monitor the motion of the shoulder and the elbow. We conducted a user study with ten volleyball players for a total of 1000 volleyball serves. We classified serving motion using a KNN with a classification accuracy of 89.2%. We will use this data provide actionable insights back to the player to help improve their serving skill. Fourth, we present BreathEZ, the first smartwatch application that provides both choking first aid instruction and real-time tactile and visual feedback on the quality of the abdominal thrust compressions. We evaluated our application through two user studies involving 20 subjects and 200 abdominal thrust events. The results of our study show that BreathEZ achieves a classification accuracy of 90.9% for abdominal thrusts. All participants that used BreathEZ in our study were able to improve their performance of abdominal thrusts. Of these participants, 60% were able to perform within the recommended range with the use of BreathEZ. Comparatively no participants trained with a video only reached that range. Finally, we present BBAid: the first smartwatch based system that provides real-time feedback on the back blow portion of choking first aid while instructing the user on first aid procedure. We evaluated our application through two user studies involving 26 subjects and 260 back blow events. The results of our study show that BBAid achieves a classification accuracy of 93.75% for back blows. With the use of BBAid, participants in our study were able to perform back blows within the recommended range 75% of the time. Comparatively the participants trained with a video only reached that range 12% of the time. All participants in the study, after receiving training were much more willing to perform choking first aid

Exercise Training for autoimmune myasthenia gravis: A review of safety and effectiveness based on existing literature

No abstract is required for a review article as per instruction