Biomedical subjects

Chris Nugent

Publications and source records attributed to Chris Nugent.

3 recordsLinked to original sources

PubMed2005

Software and knowledge engineering aspects of smart homes applied to health.

Smart Home technology offers a viable solution to the increasing needs of the elderly, special needs and home based-healthcare populations. The research to date has largely focused on the development of communication technologies, sensor technologies and intelligent user interfaces. We claim that this technological evolution has not been matched with a step of a similar size on the software counterpart. We particularly focus on the software that emphasizes the intelligent aspects of a Smart Home and the difficulties that arise from the computational analysis of the information collected from a Smart Home. The process of translating information into accurate diagnosis when using non-invasive technology is full of challenges, some of which have been considered in the literature to some extent but as yet without clear landmarks.

Aged↗

PubMed2005

Lifestyle support through efficient ECG acquisition and analysis.

People are becoming more aware of their health and the lifestyles they live. As people use computers more and more in a wide variety of occupations, they would find it desirable to monitor their lifestyle without having to leave their desk. Through the analysis of the Electrocardiogram (ECG), it is possible to obtain a person's heartrate and diagnose a number of conditions associated with abnormal heart function. To obtain an accurate heartrate, the ECG signals have to be analysed and calculations performed to find occurrences of the QRS complex, a major component of the ECG signal. This research entailed creating the software required to interpret ECG signals recorded from an innovative computer peripheral allowing recordings from the user's forearms as they operate the computer. The user could therefore effortlessly monitor their lifestyle during normal computer usage.

Computer Communication Networks↗

PubMed2005

Intelligent analysis of EMG data for improving lifestyle.

In the tragic situation when a person loses his or her hand, they are usually faced with only one option if they wish to regain a good level of mobility; learn to control an artificial hand. It has been suggested that our brain stores a "body map" of the different parts in our body. Thus, if a person loses a hand, their "body map" remains intact and produces phantom sensations that permit the person to feel like they still have their hand. Some discomfort is felt during these sensations; nevertheless, there is a positive side to them as they enable patients to control prosthetic replacements. Sensations experienced can be measured using a method known as Electromyography (EMG) and can be acquired and processed to control an artificial hand. This research involved the acquisition, analysis and classification of EMG signals through construction of a recording device and the development of classification models based on heuristic approaches and Artificial Intelligence classifiers based on Neural Networks to control artificial hands.

Algorithms↗