Study of Wearable IoT devices in 2021: Analysis &amp; Future Prospects

Bisht, Raj Kishor; Jain, Sourabh; Tewari, Naveen

doi:10.1109/iciem51511.2021.9445334

Cited by 18 publications

(5 citation statements)

References 14 publications

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“…However, wearable IoT devices have gained immense popularity in recent years. These include fitness trackers, smartwatches, and health monitors [5]. Wearables are designed to be worn directly on the body, collecting data that ranges from step counts and heart rate to sleep patterns and even location tracking [6].…”

Section: Landscapementioning

confidence: 99%

IoT Complexity: Security, Vulnerabilities and Risks

Rashid,

Haque,

Wang

2024

EJECE

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IoT privacy highlights the critical significance of tailored threat models to address the evolving challenges in the IoT landscape. This research paper presents an in-depth examination of privacy threat modeling in the context of the Internet of Things (IoT), and aims to develop threat models tailored to different IoT device categories, identifying vulnerabilities and potential privacy risks associated with each. This analysis seeks to provide insights into the diverse privacy challenges posed by IoT devices, ranging from wearables to healthcare IoT and smart home, which exhibit unique vulnerabilities and privacy risks. By developing threat models specific to each device category, this research elucidates the diversity of privacy concerns, such as data breaches, unauthorized access, and data tracking the applicability of privacy regulations varies across these categories, emphasizing the need for tailored regulatory frameworks. The research underscores the importance of user education and responsible device design, advocating for privacy literacy and transparency, as it ensures that privacy is an integral part of the development process, fostering a safer, more secure, and privacy-conscious IoT ecosystem where innovation and privacy coexist for the benefit of all.

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Section: Landscapementioning

confidence: 99%

IoT Complexity: Security, Vulnerabilities and Risks

Rashid,

Haque,

Wang

2024

EJECE

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“…Recently, the rapid development of the Internet of Things (IoT) has made great progress in the development of intelligent wearable/implantable devices [1][2][3][4][5][6]. Products such as medical and health products and somatosensory control products have put forward requirements for miniaturization, portability, and autonomous sensor systems [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

An ultra‐low quiescent current tri‐mode DC–DC boost converter with 95.6% peak efficiency for internet of things application

Zheng

Song

Guo

et al. 2023

IET Power Electronics

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An ultra‐low quiescent current tri‐mode DC–DC boost converter is proposed in this paper, which can efficiently handle loads from 1 μA to 300 mA, providing 5‐V output from 3 to 4.2‐V input. Hysteresis current mode control is adopted to realize seamless mode switching between continuous conduction mode (CCM) and discontinuous conduction mode (DCM). In order to deal with the light load situation, this paper proposes a quasi burst mode (QBM). In this mode, most of the modules are turned off and only the QBM controller, low‐power current bias and sample and hold circuit are retained, which significantly reduces the static current of the converter, and thus improves the light load efficiency. Meanwhile, the average current of error amplifier and comparator are reduced significantly by dynamic biasing. Finally, the efficiency of the converter is greatly improved and kept at a reasonable output ripple. The proposed converter is implemented in a 0.13‐μm BCD process design and manufacturing. The test results show that the quiescent current of the converter is only 780 nA, which can achieve a peak efficiency of 95.6%, and ensure that the efficiency is maintained above 80% in the load range of 10 μA to 300 mA.

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“…There is a wide range of wearable devices that can be worn on a multitude of body districts (e.g. eyes, ears, arms, wrists, hands, chest) and are specifically designed for extracting the main physiological parameters of interest for a real-time monitoring of the individual [3]. The acquired data can then be preprocessed on site and then stored or shared with other devices through wireless communication (e.g.…”

Section: Introductionmentioning

confidence: 99%

Low-invasive multisensor real-time acquisition system for the assessment of cardiorespiratory and skin conductance parameters

Volpes

Valenti

Parisi

et al. 2022

2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)

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In recent years, the attention to the health and comfort of the individual, together with the electronic miniaturization progress, have led to an increased interest in the development of biomedical devices that are able to acquire a multitude of biomedical signals. Such devices should be wearable and comfortable during daily use, to be thus suitable for continuously monitoring psychophysical health states. In this context, we have designed and realized a portable biomedical device capable of real-time acquisition of electrocardiographic (ECG), photoplethysmographic (PPG), breathing and galvanic skin response (GSR) signals, for a noninvasive monitoring of multiple physiological parameters. This work shows the architecture of our system, which integrates a Bluetooth module for wireless communication with the central computer and novel analog sensors capable of carrying out breathing and GSR measurements. Preliminary measurements carried out using our system during a controlled breathing protocol illustrated how the simultaneous measurement of ECG, PPG, GSR and respiration allows tracking changes not only in heart rate, but also in epidermal tissue sweating, thus confirming that the device can be successfully employed for monitoring health status and, in perspective, also for assessing the individual's stress level.

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Study of Wearable IoT devices in 2021: Analysis & Future Prospects

Cited by 18 publications

References 14 publications

IoT Complexity: Security, Vulnerabilities and Risks

IoT Complexity: Security, Vulnerabilities and Risks

An ultra‐low quiescent current tri‐mode DC–DC boost converter with 95.6% peak efficiency for internet of things application

Low-invasive multisensor real-time acquisition system for the assessment of cardiorespiratory and skin conductance parameters

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