2020
DOI: 10.4258/hir.2020.26.2.83
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Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health

Abstract: One way to keep track of the human body's most basic functions is by checking its vital signs, which includes body temperature, heart rate, respiration rate, and blood pressure. These variables can be monitored using wearable devices. Currently, wearable devices are on their way to their golden era. For the last couple of years, the market value of wearables has gradually climbed. The total shipment of wearable devices, including smartwatches, wrist bands, and ear-worn devices, climbed from 45.1 million units … Show more

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Cited by 25 publications
(9 citation statements)
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“…FIGURE 1 Concept of 'Layered mental healthcare'. OT is the optical topography, i.e., functional near-infrared spectroscopy device A lot of biometric measurements have been used for monitoring distress and also both bio-and neuro-feedbacks for stress coping [9]. The concept of layer is introduced here to cover a variety of preceding symptoms.…”
Section: Layered Mental Healthcarementioning
confidence: 99%
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“…FIGURE 1 Concept of 'Layered mental healthcare'. OT is the optical topography, i.e., functional near-infrared spectroscopy device A lot of biometric measurements have been used for monitoring distress and also both bio-and neuro-feedbacks for stress coping [9]. The concept of layer is introduced here to cover a variety of preceding symptoms.…”
Section: Layered Mental Healthcarementioning
confidence: 99%
“…A lot of biometric measurements have been used for monitoring distress and also both bio‐and neuro‐feedbacks for stress coping [ 9 ]. The concept of layer is introduced here to cover a variety of preceding symptoms.…”
Section: Layered Mental Healthcarementioning
confidence: 99%
See 1 more Smart Citation
“…Sufficient prior knowledge is also required to support the modeling process to achieve a high action recognition rate [11]. Depending on the type of features extracted, traditional-based action recognition methods can be further classified as human geometry-based methods, motion information-based methods, and spatiotemporal interest point-based methods [12]. Deep learning-based action recognition is an end-to-end approach that automatically learns relevant features directly from the original RGB video sequences and uses them for action classification and is divided into dual-stream convolutional neural networkbased action recognition methods, 3D convolutional neural network-based action recognition methods, and long-and short-term memory network-based action recognition methods depending on the network structure [13].…”
Section: Current Status Of Researchmentioning
confidence: 99%
“…Wearable sensing technologies have enabled us to monitor our bodily states and, given some self-discipline, improve our health [9]. The entry device for most people, and often central hub for data analysis, is their smartphone [2].…”
Section: Introductionmentioning
confidence: 99%