Self-Powered Wearable IoT Devices for Health and Activity Monitoring

Profited from the rapid development of flexible skin‐like electronic materials and artificial intelligent technology, remarkable achievements have been witnessed in wearable health monitoring devices in recent years. The wearable intelligent systems featured with tailored structures and compositions as well as enriched functions enable human beings to access to next‐generation closed‐loop platform for early disease prevention and diagnosis. In this context, this mini‐review focuses on the recent progress and applications of flexible wearable intelligent health monitoring devices. Specifically, the basic sensing mechanisms and corresponding property requirements for wearable healthcare devices are examined firstly. Secondly, the versatile applications of advanced wearable devices for detecting temperature, heart rate, blood pressure and glucose are scrutinized exclusively. Finally, a brief summary is presented accompanying with future outlook in terms of material preparation, mechanism development and integration design of monitoring systems. This manuscript is expected to provide critical guidelines to those working in skin‐like electronics, flexible sensors, wearable intelligent devices, health monitoring and other related disciplines, especially for the beginners.

Emerging intelligent wearable devices for cardiovascular health monitoring

AimTo explore the perceptions of elderly patients with chronic diseases and their healthcare providers on the use of wearable devices for home health monitoring, identifying barriers and facilitators to their effective adoption in China's rapidly aging population.BackgroundAs China's population ages, managing chronic diseases among elderly patients has become increasingly complex. Wearable health monitoring devices offer a promising solution, enabling remote and continuous health tracking. However, the adoption of these devices remains limited, particularly among elderly patients. Understanding the perspectives of both patients and healthcare providers is crucial for optimizing wearable device use in chronic disease management.DesignA qualitative descriptive study.MethodFrom May 2023 to March 2024, semistructured interviews were conducted with 16 elderly patients and 11 healthcare providers in Nanjing, China. Participants were selected through purposive sampling. Data were analyzed using Colaizzi's 7-step method, generating key themes that address both the challenges and opportunities in adopting wearable health technologies.FindingsSeven major themes emerged: (1) Technology Acceptance and Motivation, (2) Changes in Social Support and Interaction, (3) Adjustments in Healthcare Work Modes, (4) Barriers and Risks in Technology Application, (5) Device Compliance and Knowledge Gaps, (6) Identifying Key Features for Quality Assessment of Wearable Devices, and (7) The Role of Customization and Adaptability. While the potential benefits of wearable devices for chronic disease management were widely recognized, concerns about complexity, cost, and data security were key obstacles.ConclusionWearable devices hold significant potential for improving the management of chronic diseases among elderly patients, yet multiple barriers hinder their widespread adoption. Addressing issues related to usability, privacy, and affordability, alongside providing education and policy support, will be critical to enhancing their integration into healthcare settings.Implications for the Profession and Patient CareThis study underscores the importance of creating targeted strategies to overcome the challenges in using wearable health devices among elderly patients. Healthcare providers and policymakers should focus on simplifying technology, enhancing patient education, and addressing privacy concerns to foster broader acceptance and use of these devices in chronic disease care.ImpactBy promoting the adoption of wearable health technologies, healthcare systems can improve chronic disease management outcomes for elderly patients, reduce the burden on healthcare services, and support a more patient-centered approach to care.Patient or Public ContributionElderly patients with chronic diseases and their healthcare providers contributed valuable insights by sharing their experiences with wearable health monitoring devices, shaping the study's findings.

The growth of IoT technology, increasing prevalence of embedded devices, and advancements in biomedical technology have led to the emergence of numerous wearable health monitoring devices (WHMDs) in clinical settings and in the community. The majority of these devices are Bluetooth Low Energy (BLE) enabled. Though the advantages offered by BLE-enabled WHMDs in tracking, diagnosing, and intervening with patients are substantial, the risk of cyberattacks on these devices is likely to increase with device complexity and new communication protocols. Furthermore, vendors face risk and financial tradeoffs between speed to market and ensuring device security in all situations. Previous research has explored the security and privacy of such devices by manually testing popular BLE-enabled WHMDs in the market and generally discussed categories of possible attacks, while mostly focused on IP devices. In this work, we propose a new semi-automated framework that can be used to identify and discover both known and unknown vulnerabilities in WHMDs. To demonstrate its implementation, we validate it with a number of commercially available BLE-enabled enabled wearable devices. Our results show that the devices are vulnerable to a number of attacks, including eavesdropping, data manipulation, and denial of service attacks. The proposed framework could therefore be used to evaluate potential devices before adoption into a secure network or, ideally, during the design and implementation of new devices.

A wearable H-shirt for exercise ECG monitoring and individual lactate threshold computing

The use of wearable and mobile devices for health and activity monitoring is growing rapidly. These devices need to maximize their accuracy and active time under a tight energy budget imposed by battery and form-factor constraints. This paper considers energy harvesting devices that run on a limited energy budget to recognize user activities over a given period. We propose a technique to co-optimize the accuracy and active time by utilizing multiple design points with different energy-accuracy trade-offs. The proposed technique switches between these design points at runtime to maximize a generalized objective function under tight harvested energy budget constraints. We evaluate our approach experimentally using a custom hardware prototype and 14 user studies. It achieves 46% higher expected accuracy and 66% longer active time compared to the highest performance design point.

Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect

Wearable health monitoring devices have been widely explored to enable continuous monitoring of physiological vital signals, such as electrocardiogram (ECG). In this work, we investigate the applicability of ECG signals from such wearable devices in human identification. In the 5-subject study we undertook, the proposed method exhibits near-100% recognition rates based on single heartbeats, even with a six-month interval between the training and testing data. This indicates that ECG signals can be used as robust biometrics and as an automatic login solution for such wearable health monitoring devices.

The use of wearable devices for remote health monitoring is a rapidly expanding field. These devices might benefit patients and providers; however, they are not yet widely used in healthcare. This scoping review assesses the current state of the literature on wearable devices for remote health monitoring in non-hospital settings. CINAHL, Scopus, Embase and MEDLINE were searched until August 5, 2024. We performed citation searching and searched Google Scholar. Studies on wearable devices in an outpatient setting with a clinically relevant, measurable outcome were included and were categorized according to intended use of data: monitoring of existing disease vs. diagnosis of new disease. Eighty studies met eligibility criteria. Most studies used device data to monitor a chronic disease (68/80, 85%), most often neurodegenerative (22/68, 32%). Twelve studies (12/80, 15%) used device data to diagnose new disease, majority being cardiovascular (9/12, 75%). A range of wearable devices were studied with watches and bracelets being most common (50/80, 63%). Only six studies (8%) were randomized controlled trials, four of which (67%) showed evidence of positive clinical impact. Feasibility determinants were inconsistently reported, including compliance (51/80, 64%), patient-reported useability (13/80, 16%), and participant technology literacy (1/80, 1%). Evidence for clinical effectiveness of wearable devices remains scant. Heterogeneity across studies in terms of devices, disease targets and monitoring protocols makes data synthesis challenging, especially given the rapid pace of technical innovation. These findings provide direction for future research and implementation of wearable devices in healthcare.

In the context of the booming wearable device industry, wearable devices equipped with diverse biosensors have rapidly advanced, leveraging portability, real-time monitoring, and accurate detection. These diverse devices can measure multiple health data, achieving various monitoring goals. This paper focuses on categorizing and summarizing the application scenarios of three major types of wearable devices for daily health monitoring. Employing a literature review methodology, this research retrieved, screened, categorized, and summarized articles from academic websites such as CNKI and Web of Science, introducing the detection targets of wearable devices primarily utilizing optical sensors, piezoelectric sensors, and electrochemical sensors. The application scenarios are divided into daily monitoring for healthy individuals and those with chronic conditions, with detailed analyses based on specific scenarios such as sleep, exercise monitoring, cardiovascular diseases, diabetes, Sleep Apnea Hypopnea Syndrome (SAHS), and fall prevention for the elderly. This research summarizes the advantages (portability, real-time monitoring, non-invasiveness) and limitations (accuracy improvement needed, susceptibility to environmental factors, individual differences neglected) of wearable devices. Finally, it outlines future directions for optimizing performance and user convenience, including intuitive diagnostic displays and aesthetic designs.

A negative-work knee energy harvester based on homo-phase transfer for wearable monitoring devices

Wearable health monitoring devices are becoming increasingly ubiquitous in clinical settings and even in monitoring daily activities. This recent spurt in wearable devices has been made possible through the development of low power electronics, small footprint components and efficient data transmission methods. The next big step in making monitoring devices more 'wearable' is the elimination of batteries. Without the need to replace and recharge batteries, monitoring can be uninterrupted and the monitoring device itself can be seamlessly integrated into garments. However, to achieve this goal, merely reducing sensor power consumption is not enough. There is a need for unconventional methods of health monitoring. par In this work, a novel passive Radio Frequency Identification (RFID) based method for transmitting health parameters wirelessly and without batteries is described. The dissertation proposes an innovative method of transmitting health parameter data by simply turning RFID tags on and off. Technology for RFID based continuous monitoring that include a wireless power harvester and low-power circuits for amplification and health parameter detection are developed in this research. The dissertation includes practical applications of the technology that are demonstrated using heart rate and uterine contraction monitoring as examples. Empirical tests for characterizing the heart rate monitoring system are also conducted. The heart rate monitoring technology is validated with human testing which showed a correlation of over 99% between actual and detected heart rate data.

Recent developments in stretchable and flexible sensing and processing technologies enable a wide range of wearable devices. These devices can pave the way to medical applications ranging from health and activity monitoring to diagnosis and treatments of movement disorders. However, recent studies show that this potential is hindered by both adaptation challenges that affect the end users and technology challenges faced by developers. This paper first summarizes the challenges faced by wearable devices targeting health and user activity monitoring applications. Then, it reviews recent research progress towards addressing these challenges in energy harvesting, energy management, flexible system design, and test areas.

Developing an intelligent IoT-enabled wearable multimodal biosensing device and cloud-based digital dashboard for real-time and comprehensive health, physiological, emotional, and cognitive monitoring using multi-sensor fusion technologies

Flexible thermoelectric generators (f‐TEGs) have demonstrated great potential in wearable self‐powered health monitoring devices. However, the existing wearable f‐TEGs are neither flexible enough to bend and stretch while maintaining the device's integrity with a good TE performance nor directly compatible with clothes materials. Here, ultraflexible fabric‐based thermoelectric generators (uf‐TEGs) are proposed with conductive cloth electrodes and elastic fabric substrate. The patterned elastic fabric substrate fits the rigid cuboids well, together with serpentine structured cloth electrodes, rendering uf‐TEG with excellent integrity and flexibility, thereby achieving a highly functional TE performance when strain reaches 30% or on arbitrarily shaped heat sources. The uf‐TEGs show a large peak power of 64.10 μW for a temperature difference of 33.24 K with a high voltage output of 111.49 mV, which is superior compared to previously reported fabric‐based TEG devices, and it is still functional after the water immersion test. Besides the energy harvesting function, with both the temperature sensing ability and the touch perception, this uf‐TEG is demonstrated as the electrical skin when mounted on a robot. Moreover, due to the wind‐sensitive performance and self‐power ability, the uf‐TEGs are assembled on cloth as wearable health and motion monitoring devices.