On A1c and its dependence on PG level.
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Blood Glucose↗
Biomedical subjects
Oliver Gibson
Publications and source records attributed to Oliver Gibson.
On the analysis of single versus multiple channels of electromagnetic brain signals.
OBJECTIVE: When extracting information from electromagnetic (EM) brain function through recordings such as the electroencephalogram (EEG) it is often assumed that signal processing techniques must be applied to multiple simultaneous recordings in order to obtain useful results. However, sometimes only a single channel of EEG recording is available or desirable. In this paper we objectively assess a novel methodology which exploits only a single measurement channel to extract information of interest relatively independent of channel location (relative to the source of interest). METHODS: The method relies on a combination of a matrix of delay vectors constructed from the single channel measurement, along with constrained independent component analysis, which incorporates prior information into the process. MATERIALS: Here, we use synthetically generated seizure EEG, composed of real, normal multi-channel EEG onto which is superimposed synthetic epileptic "seizure-like" activity, at different signal-to-noise (SNR) levels, through an equivalent current dipole model. RESULTS: We show that the method can extract desired information from single channels with a reasonable accuracy even at very small SNR and from channels distant from the focus of the activity. This provides a powerful technique capable of extracting multiple sources underlying single channel recordings and will be useful in situations where only single channel EM recordings of brain function are desirable, such as would be the case in wearable or implantable recording devices.
Artificial Intelligence↗
A real-time, mobile phone-based telemedicine system to support young adults with type 1 diabetes.
Telemedicine systems have been proposed as a means of supporting people with diabetes in the self-management of their condition. Requirements for monitoring parameters of care, including glycaemic control, extent of analysis and interpretation of data, patient-clinician contacts, and involvement of a multidisciplinary care team with effective communication, can be addressed by telemedicine systems. We describe the development and implementation of an innovative real-time telemedicine system based around transmission and feedback of data to and from a mobile phone. Proprietary Java-based programs were used to link a blood glucose meter to a mobile phone. In addition to immediate transmission of blood glucose data, information about insulin dose, eating patterns and physical exercise were collected. Immediate feedback to the phone included a colour histogram to draw attention to levels of control over glycaemia over the previous two weeks. Clinicians supporting patients had access to summary screens identifying users not testing, and those with levels of blood glucose outside pre-defined limits. More detailed graphical displays of data were used to provide data about control of insulin dose and the degree to which it was modified in response to diet and exercise. The system has been evaluated in a clinical trial conducted in secondary care and is now being adapted for use in a trial in primary care, which is designed to assess its effectiveness in providing integrated management for the patient, general practitioner and pharmacist.
Adolescent↗