Wireless temporal artery bandage thermometer

Finvers, I.G.; Haslett, J.W.; Jullien, G.A.

doi:10.1109/biocas.2006.4600334

Cited by 9 publications

(11 citation statements)

References 5 publications

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“….. It is noted that the proposed model is concerned with the deviation in the temperature samples, and not with the absolute temperatures like [11]- [13].…”

Section: Prior Workmentioning

confidence: 95%

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A Simple Iterative Algorithm for Wellness Applications

Kailas

Chong²,

Watanabe³

2010

2010 IEEE Wireless Communication and Networking Conference

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The concept of "wellness mobile" is one wherein wireless handheld devices such as cell phones are equipped with "wellness monitoring," thereby enabling real-time self-wellness monitoring by the cell phone user. However, this new technology is still in its infancy, and developing quantifiable measures of wellness and designing intelligent monitoring systems is quite challenging. The overriding purpose of this paper is to propose a simple wellness monitoring algorithm. The novel algorithm iteratively computes and tracks the variations in clusters of biometric measurements aiding in effective wellness management. Stress is a key indicator of wellness in human beings, and is widely regarded as a prime contributor to performance degradation and errors during various human activities.The proposed algorithm tracks the deviations in clusters of skin temperatures measurements during different activities to infer the stress states in humans. The advantage is that this simple algorithm can be implemented on handheld devices by deploying existing biometric sensors that are available in most smart phones today. This will provide cellular phones users an application to monitor their stress states easily and consistently in a non-invasive way because a stressed-out lifestyle is rarely a healthy one.

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“….. It is noted that the proposed model is concerned with the deviation in the temperature samples, and not with the absolute temperatures like [11]- [13].…”

Section: Prior Workmentioning

confidence: 95%

“…Finvers et. al., designed a bandage based thermometer placed on the temple region of the forehead to measure the core body temperature in a non-invasive manner to track the patient wellness [13]. However, all these approaches focus on tracking the instantaneous variations of a single or multiple physiological quantities.…”

Section: Prior Workmentioning

confidence: 99%

A Simple Iterative Algorithm for Wellness Applications

Kailas

Chong²,

Watanabe³

2010

2010 IEEE Wireless Communication and Networking Conference

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“…Using this assumption, equation6 becomes T c = T s . This approximation is still a topic of investigation [4].…”

Section: Arterial Blood Pressure Heart Rate Variability and Breatmentioning

confidence: 99%

Non-invasive health monitoring system (NIHMS)

Doyle

Kalsi

Aiyush

et al. 2009

2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH)

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As the population ages, there is a greater need to develop clinical and personal diagnostic tools. As wait times for medical attention increases, the automation of non-invasively collecting patient vitals could significantly improve the efficiency of modern health care. Combine the collection of these vitals with a system that can present a summary of possible diagnostic conclusions and the time spent in a waiting room can be better utilized to aid both the patient and the medical professional. This system measures the electro-ocular movement, temperature, blood oxygen saturation, arterial blood pressure, heart rate variability, and breathing rate. The measurements are combined using an embedded microcontroller that is wirelessly linked to a base station processor via Bluetooth. The system components are presented and their efficacy discussed, along with suggested enhancements.

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“…3, the simulation model was divided into five parts: the skin layer, fat layer, bone layer, insulator, and cover. A human tissue layer was established to model the forehead, which is one of the most common sites for measuring deep body temperature because the anatomy is relatively similar across individuals (Finvers et al, 2006;Werner et al, 2009;Zeiner et al, 2010). The forehead model was derived from a previous study (Steck et al, 2011).…”

Section: Simulation Model and Design Factorsmentioning

confidence: 99%