A Smart IoT-Based Prototype System for Rehabilitation Monitoring

Smart healthcare is growing significantly in the healthcare sector due to the Internet of Things. A remote monitoring system is one of the smart healthcare implementations for rehabilitating stroke patients. Nowadays, as the COVID-19 pandemic continues to spread, patients undergoing home rehabilitation have difficulty meeting with their physicians due to movement constraints. In addition, the healthcare facilities are devoted to treating patients with COVID-19. As a result, physicians and patients could not frequently meet to gather their rehabilitation progress. This study involves developing a prototype to monitor a post-stroke patient's rehabilitation process using the Arduino Nano 33 Bluetooth Low Energy (BLE) and force-sensing resistor (FSR). The prototype analyzes critical aspects of the rehabilitation process based on handgrip, heart rate, sleep, and step tracking measurements. The results of the handgrip, heart rate, sleep, and step tracking measurements are evaluated for various types of subjects and six testing approaches showed an accurate and consistent results. However, experiments partially success with a small error is detected while tracking the steps of each subject. Several recommendations are highlighted to improve the prototype using other sensors such as force sensing resistor and flex sensor for handgrip force transducer, electromyogram (EMG) sensor for stroke-patients rehabilitation, and others

A Smart IoT-Based Prototype System for Rehabilitation Monitoring

Smart healthcare is growing significantly in the healthcare sector due to the Internet of Things. A remote monitoring system is one of the smart healthcare implementations for rehabilitating stroke patients. Nowadays, as the COVID-19 pandemic continues to spread, patients undergoing home rehabilitation have difficulty meeting with their physicians due to movement constraints. In addition, the healthcare facilities are devoted to treating patients with COVID-19. As a result, physicians and patients could not frequently meet to gather their rehabilitation progress. This study involves developing a prototype to monitor a post-stroke patient's rehabilitation process using the Arduino Nano 33 Bluetooth Low Energy (BLE) and force-sensing resistor (FSR). The prototype analyzes critical aspects of the rehabilitation process based on handgrip, heart rate, sleep, and step tracking measurements. The results of the handgrip, heart rate, sleep, and step tracking measurements are evaluated for various types of subjects and six testing approaches showed an accurate and consistent results. However, experiments partially success with a small error is detected while tracking the steps of each subject. Several recommendations are highlighted to improve the prototype using other sensors such as force sensing resistor and flex sensor for handgrip force transducer, electromyogram (EMG) sensor for stroke-patients rehabilitation, and others

Towards the internet of smart clothing: a review on IoT wearables and garments for creating intelligent connected e-textiles

[Abstract] Technology has become ubiquitous, it is all around us and is becoming part of us. Togetherwith the rise of the Internet of Things (IoT) paradigm and enabling technologies (e.g., Augmented Reality (AR), Cyber-Physical Systems, Artificial Intelligence (AI), blockchain or edge computing), smart wearables and IoT-based garments can potentially have a lot of influence by harmonizing functionality and the delight created by fashion. Thus, smart clothes look for a balance among fashion, engineering, interaction, user experience, cybersecurity, design and science to reinvent technologies that can anticipate needs and desires. Nowadays, the rapid convergence of textile and electronics is enabling the seamless and massive integration of sensors into textiles and the development of conductive yarn. The potential of smart fabrics, which can communicate with smartphones to process biometric information such as heart rate, temperature, breathing, stress, movement, acceleration, or even hormone levels, promises a new era for retail. This article reviews the main requirements for developing smart IoT-enabled garments and shows smart clothing potential impact on business models in the medium-term. Specifically, a global IoT architecture is proposed, the main types and components of smart IoT wearables and garments are presented, their main requirements are analyzed and some of the most recent smart clothing applications are studied. In this way, this article reviews the past and present of smart garments in order to provide guidelines for the future developers of a network where garments will be connected like other IoT objects: the Internet of Smart Clothing.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED341D R2016/012Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2013-47141-C4-1-RAgencia Estatal de Investigación de España; TEC2016-75067-C4-1-RAgencia Estatal de Investigación de España; TEC2015-69648-RED

Discrete Chaotic Fuzzy Neural Network (DC-FNN) Based Smart Watch Embedded Devices for Sports and Health Monitoring

Improved athletic performance is expected to result from the convergence of semiconductor technology from the wearable device equipped with physiology and its clinical and translation tools. The increasing usage of smart wearable devices has made an impact not only on the lifestyle of the users, but also on biological research and personalized healthcare services.This research optimises the usage of smart watch integrated devices through wireless connection, which sheds light on wearable sensors used in sports medicine. The major objective of this article is to provide a recommended method of using wearable technology for evaluating the efficacy of health and sports monitoring. Any sport at any level may stand to profit from this embedded technology, as might academic research labs, sports medicine practises, and professional sports teams all working toward the same goal of improving player and team performance. As the primary data generated by wearable devices include the heartbeat rate, step count, and energy consumed, researchers have concentrated on associating cardiovascular disorders with these data. A Discrete Chaotic Fuzzy Neural Network (DC-FNN) model was presented to analyse smart watch functionality for use in fitness and health tracking. This study used machine learning algorithm for analyzing the performance of wearing smart watch embedded device among sports players. The study employs discrete chaotic Fuzzy neural network for evaluating the recognition time and efficiency of the embedded device. The Discrete Chaotic Fuzzy Neural Network (DC-FNN) theories focus on the expertise and experience of specialists who understand how sports system works in different parameters. The major elements of the DC-FNN strategy are based mostly on expert expertise. This research work highlights how wearable sensors can help players and trainers keep tabs on athletes\u27 biomechanical and physiological health in real time, preventing or delaying the start of injuries and providing a more accurate picture of how they are doing. Athlete involvement risk is mediated by the interplay between tissue health and training

Architecture and Applications of IoT Devices in Socially Relevant Fields

Number of IoT enabled devices are being tried and introduced every year and there is a healthy competition among researched and businesses to capitalize the space created by IoT, as these devices have a great market potential. Depending on the type of task involved and sensitive nature of data that the device handles, various IoT architectures, communication protocols and components are chosen and their performance is evaluated. This paper reviews such IoT enabled devices based on their architecture, communication protocols and functions in few key socially relevant fields like health care, farming, firefighting, women/individual safety/call for help/harm alert, home surveillance and mapping as these fields involve majority of the general public. It can be seen, to one's amazement, that already significant number of devices are being reported on these fields and their performance is promising. This paper also outlines the challenges involved in each of these fields that require solutions to make these devices reliableComment: 1

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

Networking Architecture and Key Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey

Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only virtually replicate a system's detailed operations but also analyze the current condition, predict future behaviour, and refine the control optimization. Although DT has been widely implemented in various fields, such as smart manufacturing and transportation, its conventional paradigm is limited to embody non-living entities, e.g., robots and vehicles. When adopted in human-centric systems, a novel concept, called human digital twin (HDT) has thus been proposed. Particularly, HDT allows in silico representation of individual human body with the ability to dynamically reflect molecular status, physiological status, emotional and psychological status, as well as lifestyle evolutions. These prompt the expected application of HDT in personalized healthcare (PH), which can facilitate remote monitoring, diagnosis, prescription, surgery and rehabilitation. However, despite the large potential, HDT faces substantial research challenges in different aspects, and becomes an increasingly popular topic recently. In this survey, with a specific focus on the networking architecture and key technologies for HDT in PH applications, we first discuss the differences between HDT and conventional DTs, followed by the universal framework and essential functions of HDT. We then analyze its design requirements and challenges in PH applications. After that, we provide an overview of the networking architecture of HDT, including data acquisition layer, data communication layer, computation layer, data management layer and data analysis and decision making layer. Besides reviewing the key technologies for implementing such networking architecture in detail, we conclude this survey by presenting future research directions of HDT

PhysioAR: smart sensing and augmented reality for physical rehabilitation

The continuous evolution of technology allows for a better analysis of the human being. In certain medical areas such as physiotherapy is required a correct analysis of the patient's evolution. The development of Information and Communication Technologies and recent innovations in the Internet of Things opens new possibilities in the medical field as systems of remote monitoring of patients with new sensors that allow the correct analysis of the health data of patients. In physiotherapy one of the most common problems in the application of treatments is the patient demotivation, something that today can be reduced with the introduction of Augmented Reality that provides a new experience to the patient. For this purpose, a system was developed that combines intelligent sensors with Augmented Reality application that will help monitor patient performance. This system is capable of monitoring lower limb movements acceleration, knee joint angle, patient equilibrium, muscular activity and cardiac activity using electromyography and electrocardiography with a wearable set of tools for easy utilization.A evolução continua da tecnologia permite cada vez mais uma melhor análise do ser humano. Em certas áreas médicas, como a fisioterapia, é necessária uma correta análise da evolução do paciente. O desenvolvimento das Tecnologias de Informação e Comunicação, e as inovações no domínio de Internet das Coisas novas possibilidades no ramo da medicina, como sistemas de monitorização remota de pacientes com novos sensores que permitem a correta análise dos dados de saúde dos pacientes. Na fisioterapia um dos problemas mais comuns na aplicação dos tratamentos é a desmotivação do paciente, algo que hoje pode ser reduzido com introdução da aplicação da Realidade Aumentada que proporciona uma nova experiência ao paciente. Para isso nesta dissertação foi desenvolvido um sistema que combina sensores inteligentes com Realidade Aumentada que vai ajudar o paciente monitorizando o seu desempenho. Este sistema é capaz de monitorizar o ângulo do joelho, captar acelaração de movimentos dos membros inferiores, equilíbrio do paciente, atividade muscular e atividade cárdica usando electromiografia e electrocardiografia num conjunto wearable de fácil utilização

A NEW TELEREHABILITATION SYSTEM BASED ON INTERNET OF THINGS

Internet of Things (IoT) applied in healthcare system has huge potential to improve patients' quality of life. Representing network of devices embedded with electronics and sensors, IoT enables constant monitoring of vital body functions, tracking of physical activities of a person and aides rehab physical therapy. Such an IoT-based system would allow standalone recovery process, minimizing need of dedicated medical personnel and could be used in both hospital and home conditions. In this paper, we  present a telerehabilitation system that uses wearable muscle sensor and Microsoft Kinect to create interactive personalized physical therapy that can be carried out at home. Early experiments and results of pilot implementation validate the feasibility and effectiveness of the proposed IoT-enabled telerehabilitation system

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications