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... research lab contexts. Technology has continued to advance, enabling smaller size, weight, power, and cost. The development of an ever-growing number of sports and health monitoring apps for our smartphones that interact with bio-signals obtained via smartphones, smartwatches, or other sensor devices is a direct result of this rapid proliferation . The availability of bio- signals in various circumstances has been made possible through wearable technology. Additionally, the usage of bio- sensing platforms outside of the clinical setting aids in the transformation of conventional research methods into fresh goods and services. An overview of various physiological signals and the sensors used for their measurement and quantification has been enumerated in Table 1. ...Similar publications
Regular blood pressure (BP) monitoring is the keystone to early prevention of hypertension, a major factor of heart-related disease and the leading cause of mortality worldwide. As human health is of the utmost concern, tremendous efforts have been made to advance health monitoring devices over time. At present, various techniques, broadly classifi...
Objective
This scoping review explores patients’ experience with wearable technology. Its aims are to: (a) examine studies that contain empirical findings related to patients’ experience with wearables; (b) compare these findings within and across studies; and (c) identify areas in need of greater understanding.
Methods
A Preferred Reporting Items...
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Breast cancer is the most prevalent form of tumor in women, and this is the leading cause of mortality in women. Accurately detecting and classifying breast cancer is crucial for effective treatment and diagnosis preparation. Internet of Things (IoT) wearable devices (smart bra) are considered one of the best methods for early detection and, thereb...
With the rapid development of human‐friendly wearable devices, energy storage components are required to have skin‐like stretchability or free‐form to fit closer and more comfortably to the human body. This study introduces a hierarchically interpenetrated reentrant microcellular structure combined with 2D cellular graphene/MXene/carbon nanotubes (...
Citations
This study introduces a low-power analog integrated Euclidean distance radial basis function classifier. The high-level architecture is composed of several Manhattan distance circuits in connection with a current comparator circuit. Notably, each implementation was designed with modularity and scalability in mind, effectively accommodating variations in the classification parameters. The proposed classifier’s operational principles are meticulously detailed, tailored for low-power, low-voltage, and fully tunable implementations, specifically targeting biomedical applications. This design methodology materialized within a 90 nm CMOS process, utilizing the Cadence IC Suite for the comprehensive management of both the schematic and layout design aspects. During the verification phase, post-layout simulation results were meticulously cross-referenced with software-based classifier implementations. Also, a comparison study with related analog classifiers is provided. Through the simulation results and comparative study, the design architecture’s accuracy and sensitivity were effectively validated and confirmed.
