Healthy Aims: Developing New Medical Implants and Diagnostic Equipment

Hodgins, Diana; Bertsch, Arnaud; Post, Nikki; Frischholz, M.; Volckaerts, B.; Spensley, John; Wasikiewicz, Jaroslaw M.; Higgins, Henry; Stetten, Felix von; Kenney, Laurence

doi:10.1109/mprv.2008.8

Cited by 51 publications

(30 citation statements)

References 9 publications

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“…In the first category [10,2], various wearable sensors, such as accelerometers, gyroscopes, proximity sensors and e-textile sensors, could be attached to the subject of interest to monitor vital signs such the heart beats, the respiration, the blood pressure and the glucose level and the muscle activity. In [16] the authors used a chest strap and a wristband wearable devices to analyze the sleep patterns, and to identify the most relevant sleep parameters for stress detection.…”

Section: Related Workmentioning

confidence: 99%

Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network

Eldib

Deboeverie

Philips

et al. 2015

Human Behavior Understanding

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Abstract. Nearly half of the senior citizens report difficulty initiating and maintaining sleep. Frequent visits to the bathroom in the middle of the night is considered as one of the major reasons for sleep disorder. This leads to serious diseases such as depression and diabetes. In this paper, we propose to use a network of cheap low-resolution visual sensors (30 × 30 pixels) for long-term activity analysis of a senior citizen in a service flat. The main focus of our research is on elderly behaviour analysis to detect health deterioration. Specifically, this paper treats the analysis of sleep patterns. Firstly, motion patterns are detected. Then, a rule-based approach on the motion patterns is proposed to determine the wake up time and sleep time. The nightly bathroom visit is identified using a classification-based model. In our evaluation, we performed experiments on 10 months of real-life data. The ground truth is collected from the diaries in which the senior citizen wrote down his sleep time and wake up time. The results show accurate extraction of the sleep durations with an overall Mean Absolute Error (MAE) of 22.91 minutes and Spearman correlation coefficient of 0.69. Finally, the nightly bathroom visits analysis indicate sleep disorder in several nights.

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Section: Related Workmentioning

confidence: 99%

Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network

Eldib

Deboeverie

Philips

et al. 2015

Human Behavior Understanding

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“…The scope of these researches ranges from standardization activities for telemedicine deployment (Choi et al, 2006), privacy and security solutions (Xiao et al, 2006) to realization of a system (Hodgins et al, 2008;Poon et al, 2006;Garawi et al, 2006). The main concerns of these solutions consist in assisting elders in their routine life activities, constant monitoring of their health conditions, and prompt alerting in emergency events.…”

Section: Related Workmentioning

confidence: 99%

An Advanced Home Eldercare Service

Taleb

Bottazzi

Nait-Charif

2009

Proceedings of the International Conference on Health Informatics

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Abstract:With the increase of welfare cost all over the developed world, there is a need to resort to new technologies that could help reduce this enormous cost and provide some quality eldercare services. This paper presents a middleware-level solution that integrates monitoring and emergency detection solutions with networking solutions. The proposed system enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and provides a framework for creating and managing rescue teams willing to assist elders in case of emergency situations. A prototype of the proposed system was designed and implemented. Results were obtained from both computer simulations and a real-network testbed. These results show that the proposed system can help overcome some of the current problems and help reduce the enormous cost of eldercare service.

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“…3 Recent developments of low power consumption devices enabled the realization of wireless tissue and in-body implants. The possibility to address implants wirelessly extended their application potential enormously, with numerous systems already available, including drug-delivery platforms, 4 cochlear implants, 5 pressure monitors in the brain cavity, 6 glaucoma sensors, 6,7 retinal implants, 6,8,9 brain-to-nerve interconnections for cerebral injuries 10 and direct control of prostheses. [11][12][13] There are several issues to consider while designing an in-body implant, for example, its power consumption, biocompatibility and the total size of the system.…”

Section: Introductionmentioning

confidence: 99%

“…For the latter, typical dimensions of in-body implants are in the centimeter range. 5,6,10 Hence, surgical treatment is unavoidable to implant the device. However, if the length of the device is~5 mm and the diameter is o0.5 mm, the device can be readily implanted using standard medical syringes, greatly minimizing discomfort during and after an implantation.…”

Section: Introductionmentioning

confidence: 99%

Compact helical antenna for smart implant applications

2015

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Smart implants are envisioned to revolutionize personal health care by assessing physiological processes, for example, upon wound healing, and communicating these data to a patient or medical doctor. The compactness of the implants is crucial to minimize discomfort during and after implantation. The key challenge in realizing small-sized smart implants is high-volume cost-and time-efficient fabrication of a compact but efficient antenna, which is impedance matched to 50 Ω, as imposed by the requirements of modern electronics. Here, we propose a novel route to realize arrays of 5.5-mm-long normal mode helical antennas operating in the industry-scientific-medical radio bands at 5.8 and 2.4 GHz, relying on a self-assembly process that enables large-scale high-yield fabrication of devices. We demonstrate the transmission and receiving signals between helical antennas and the communication between an antenna and a smartphone. Furthermore, we successfully access the response of an antenna embedded in a tooth, mimicking a dental implant. With a diameter of~0.2 mm, these antennas are readily implantable using standard medical syringes, highlighting their suitability for in-body implant applications.

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Healthy Aims: Developing New Medical Implants and Diagnostic Equipment

Cited by 51 publications

References 9 publications

Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network

Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network

An Advanced Home Eldercare Service

Compact helical antenna for smart implant applications

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