A Wireless Health Monitoring System Using Mobile Phone Accessories

Mahmud, Md Shaad; Wang, Honggang; Esfar-E-Alam, A M; Fang, Hua

doi:10.1109/jiot.2016.2645125

Cited by 107 publications

(30 citation statements)

References 44 publications

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“…Paper [15], presented the health monitoring using smart phone accessories. The major benefit to using this system is that the users do not have to carry an extra device while maintaining their health and safety.…”

Section: Related Workmentioning

confidence: 99%

Wireless Wearable Smart Healthcare Monitoring using Android

Mahadevaswamy¹

2018

IJCNIS

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Abstract-The healthcare monitoring system is very useful for the old age people, cardiac vascular endues and many others for observing vital parameters like blood pressure, heart rate, pulse rate, body temperature etc. The proposed work utilizes 8bit X-Mega2560 microcontroller with an application created for overseers and hospital to constantly watch the patient's parameters from their home, hospitals etc. The proposed system senses the vital parameters of the patients and sends an alert message to respective caretakers, through Wi-Fi which utilizes COAP conventions. These models are integrated to a simple arduino uno microcontroller to exhibit different functionalities. The system will reduce the cost, empowering the patients who are not able to consult the doctors for diagnosis and also minimize the patient's transportations. This system will bridge the gap between patient and doctor in real time.

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Section: Related Workmentioning

confidence: 99%

Wireless Wearable Smart Healthcare Monitoring using Android

Mahadevaswamy¹

2018

IJCNIS

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“…Hence, it can provide better services to citizens, companies, and public administration and can preserve privacy as well . The IoT has practical applications in various disciplines, including dynamic traffic light control, multinational air traffic management, and health monitoring and hence has become a technological focus for researchers in academia, industry, and government organizations.…”

Section: Introductionmentioning

confidence: 99%

“…A number of recent research papers illustrate the usefulness and efficiency of IoT applications to increase the quality of health services to the citizens of smart cities . Modernization in medical services has reduced health care cost and throng in hospitals to a great extent.…”

Section: Introductionmentioning

confidence: 99%

An automated patient monitoring using discrete‐time wireless sensor networks

Chatterjee

Biswas

Das

2020

Int J Communication

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In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature. KEYWORDSBayesian Learning, joint model, latent variable, patient monitoring, wireless sensor networks Int J Commun Syst. 2020;33:e4390.wileyonlinelibrary.com/journal/dac

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“…as smartphone [4], WiFi device [5], [6] and smart speaker [7]. For patients with Motor Neurone Disease (MND), they have difficulty moving their arms or hands, and even their speech function is severely affected, hindering their communication with these IoT devices and other people.…”

Section: Introductionmentioning

confidence: 99%

WiMorse: A Contactless Morse Code Text Input System Using Ambient WiFi Signals

Niu

Zhang

Jiang

et al. 2019

IEEE Internet Things J.

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Recent years have witnessed advances of Internet of Things (IoT) technologies and their applications to enable contactless sensing and human-computer interaction in smart homes. For people with Motor Neurone Disease (MND), their motion capabilities are severely impaired and they have difficulties interacting with IoT devices and even communicating with other people. As the disease progresses, most patients lose their speech function eventually which makes the widely adopted voicebased solutions fail. In contrast, most patients can still move their fingers slightly even after they have lost the control of their arms and hands. Thus we propose to develop a Morse code based text input system, called WiMorse, which allows patients with minimal single-finger control to input and communicate with other people without attaching any sensor to their fingers. WiMorse leverages ubiquitous commodity WiFi devices to track subtle finger movements contactlessly and encode them as Morse code input. In order to sense the very subtle finger movements, we propose to employ the ratio of the Channel State Information (CSI) between two antennas to enhance the Signal to Noise Ratio. To address the severe location dependency issue in wireless sensing with accurate theoretical underpinning and experiments, we propose a signal transformation mechanism to automatically convert signals based on the input position, achieving stable sensing performance. Comprehensive experiments demonstrate that WiMorse can achieve higher than 95% recognition accuracy for finger generated Morse code, and is robust against input position, environment changes, and user diversity.

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A Wireless Health Monitoring System Using Mobile Phone Accessories

Cited by 107 publications

References 44 publications

Wireless Wearable Smart Healthcare Monitoring using Android

Wireless Wearable Smart Healthcare Monitoring using Android

An automated patient monitoring using discrete‐time wireless sensor networks

WiMorse: A Contactless Morse Code Text Input System Using Ambient WiFi Signals

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