Evaluation of a technology enabled garment for older walkers.

Walking is often cited as the best form of activity for persons over the age of 60. In this paper we outline the development and evaluation of a smart garment system that aims to monitor the wearer's wellbeing and activity regimes during walking activities. Functional requirements were ascertained using a combination of questionnaires and two workshops with a target cohort. The requirements were subsequently mapped onto current technologies as part of the technical design process. In this paper we outline the development and second round of evaluations of a prototype as part of a three-phase iterative development cycle. The evaluation was undertaken with 6 participants aged between 60 and 73 years of age. The results of the evaluation demonstrate the potential role that technology can play in the promotion of activity regimes for the older population.

Mining, knowledge and decision support.

Decision support systems (DSS) are software entities that assist the physician in the decision making process. They have found application in medicine due to the large amounts of data (e.g. laboratory measurements such as blood pressure, heart rate, body-mass index) and information (e.g. patient history, population statistics based on age and sex) that must be considered before diagnosing any disease or recommending a therapy. A well known example is the embedded software in defibrillators which allows a 'shock' to be delivered, by analyzing the electrocardiogram for known conditions (heart attack). The shock can restart the heart and timely delivery can resuscitate the patient. As well as assisting in primary diagnosis, a DSS can reduce medical error, assist compliance with clinical guidelines, improve efficiency of care delivery and improve quality of care. Decision support still has significant acceptance issues in clinical routine, but can achieve more prominence, as systems are demonstrated to provide effective knowledge based support. Data mining is often used to provide some insight to a data set and update our accepted knowledge. In this section, we discuss a study which examines where electrocardiographic information should be recorded from a patient's torso in order to increase diagnostic yield.

Optimal electrocardiographic lead systems: practical scenarios in smart clothing and wearable health systems.

Advances in wearable health systems, from a smart textile, signal processing, and wireless communications perspective, have resulted in the recent deployment of such systems in real clinical and healthcare settings. Nevertheless, the problem of identifying the most appropriate sites from which biological parameters can be recorded still remains unsolved. This paper aims to asses the effects of various practical constraints that may be encountered when choosing electrocardiographic recording sites for wearable health systems falling within the category of smart shirts for cardiac monitoring and analysis. We apply a lead selection algorithm to a set of 192 lead body surface potential maps (BSPM) and simulate a number of practical constraints by only allowing selection of recording sites from specific regions available in the 192 lead array. Of the various scenarios that were investigated, we achieved the best results when the selection process to identify the recording sites was constrained to an area around the precordial region. The top ten recording sites chosen in this region exhibited an rms voltage error of 25.8 mu V when they were used to estimate total ECG information. The poorest performing scenario was that which constrained the selection to two vertical strips on the posterior surface. The top ten recording sites chosen in this scenario exhibited an rms voltage error of 41.1 muV. In general, it was observed that out of all the scenarios investigated, those which constrained available regions to the posterior and lateral surfaces performed less favorably than those where electrodes could also be chosen on the anterior surface. The overall results from our approach have validated the proposed algorithm and its ability to select optimal recording sites taking into consideration the practical constraints that may exist with smart shirts.

Personalisation and configuration of assistive technologies.

In this paper we present a multimedia tool that allows personalisation and configuration of an assistive technology. We have developed a tool called HomePUI that allows configuration of three disease domains; cognitive, physical and chronic. In this paper we present the rationale for our work, details of the developed tool and also present two case studies in which the tool has been used within cognitive and chronic disease management domains.

Synthesising the 12-lead electrocardiogram: Trends and challenges.

An area of electrocardiography which has received much interest of late is that of synthesising the 12-lead ECG from a reduced number of leads. The main advantage of this approach is obvious, as fewer recording sites are required to capture the same information. This, in turn, streamlines the ECG acquisition process with little detriment to the integrity of information used for interpretation. In the current article, we provide an overview of ECG synthesis along with a description of various 'limited lead' systems that have been reported in the literature. Based on this, several suggestions as to what the ECG of the future may entail have been made.

Optimizing the 12-lead electrocardiogram: a data driven approach to locating alternative recording sites.

BACKGROUND: Despite its widespread use, the limitations of the 12-lead electrocardiogram (ECG) are undisputed. The main deficiency is that just a small area of the precordium is interrogated and for some abnormalities information may be transmitted to a region of the body surface where information is not recorded. In this study, we attempted to optimize the 12-lead ECG by using a data-driven approach to suggest alternate recording sites. METHODS: A sequential lead selection algorithm was applied to a set of 744 body surface potential maps (BSPMs), consisting of recordings from subjects with myocardial infarction, left ventricular hypertrophy, and no apparent disease. A number of scenarios were investigated in which pairs of precordial leads were repositioned; these pairs were V3 and V5, V4 and V5, and V4 and V6. The algorithm was also used to find optimal positions for all 6 precordial leads. RESULT: Through estimation of entire surface potential distributions it was found that each of the scenarios, with 2 leads repositioned, captured more information than the standard 12-lead ECG. The scenario with V4 and V6 repositioned performed best with a root mean square error of 22.3 microvolts and a correlation coefficient of 0.967. This configuration also fared favorably when compared to the scenario where all 6 precordial leads were repositioned as optimizing all 6 leads offered no significant improvement. CONCLUSION: This study demonstrated the use of a lead selection algorithm in enhancing the 12-lead ECG. The results also indicated that repositioning just 2 precordial leads can provide the same level of information capture as that observed when all precordial leads are optimally placed.

Selection of optimal recording sites for limited lead body surface potential mapping: a sequential selection based approach.

BACKGROUND: In this study we propose the development of a new algorithm for selecting optimal recording sites for limited lead body surface potential mapping. The proposed algorithm differs from previously reported methods in that it is based upon a simple and intuitive data driven technique that does not make any presumptions about deterministic characteristics of the data. It uses a forward selection based search technique to find the best combination of electrocardiographic leads. METHODS: The study was conducted using a dataset consisting of body surface potential maps (BSPM) recorded from 116 subjects which included 59 normals and 57 subjects exhibiting evidence of old Myocardial Infarction (MI). The performance of the algorithm was evaluated using spatial RMS voltage error and correlation coefficient to compare original and reconstructed map frames. RESULTS: In all, three configurations of the algorithm were evaluated and it was concluded that there was little difference in the performance of the various configurations. In addition to observing the performance of the selection algorithm, several lead subsets of 32 electrodes as chosen by the various configurations of the algorithm were evaluated. The rationale for choosing this number of recording sites was to allow comparison with a previous study that used a different algorithm, where 32 leads were deemed to provide an acceptable level of reconstruction performance. CONCLUSION: It was observed that although the lead configurations suggested in this study were not identical to that suggested in the previous work, the systems did bear similar characteristics in that recording sites were chosen with greatest density in the precordial region.

Monitoring of symptoms and interventions associated with multiple sclerosis.

We have utilized the Structured Data Entry approach to build a prototype interface for the recording of personalized symptoms associated with Multiple Sclerosis (MS). The software provides both graphical input and output, to facilitate efficient data entry and monitoring. Graphical input is transformed to textual information, which is stored in a database in a hierarchical tree structure. Pain management in MS may be achieved by careful monitoring of the symptom in response to treatment. Pain location is selected on a body image and severity and other attributes represented using a graphical visual analog scale, leading to more convenient input and a less ambiguous coding than is achievable with narrative text alone. The Internet can be used to record and provide access to clinical data, assisting the citizen by providing a healthcare professional partnership approach to care. This approach could provide an objective means of monitoring symptoms and hence provide a more personalized approach to MS management.

Mining for diagnostic information in body surface potential maps: a comparison of feature selection techniques.

BACKGROUND: In body surface potential mapping, increased spatial sampling is used to allow more accurate detection of a cardiac abnormality. Although diagnostically superior to more conventional electrocardiographic techniques, the perceived complexity of the Body Surface Potential Map (BSPM) acquisition process has prohibited its acceptance in clinical practice. For this reason there is an interest in striking a compromise between the minimum number of electrocardiographic recording sites required to sample the maximum electrocardiographic information. METHODS: In the current study, several techniques widely used in the domains of data mining and knowledge discovery have been employed to mine for diagnostic information in 192 lead BSPMs. In particular, the Single Variable Classifier (SVC) based filter and Sequential Forward Selection (SFS) based wrapper approaches to feature selection have been implemented and evaluated. Using a set of recordings from 116 subjects, the diagnostic ability of subsets of 3, 6, 9, 12, 24 and 32 electrocardiographic recording sites have been evaluated based on their ability to correctly asses the presence or absence of Myocardial Infarction (MI). RESULTS: It was observed that the wrapper approach, using sequential forward selection and a 5 nearest neighbour classifier, was capable of choosing a set of 24 recording sites that could correctly classify 82.8% of BSPMs. Although the filter method performed slightly less favourably, the performance was comparable with a classification accuracy of 79.3%. In addition, experiments were conducted to show how (a) features chosen using the wrapper approach were specific to the classifier used in the selection model, and (b) lead subsets chosen were not necessarily unique. CONCLUSION: It was concluded that both the filter and wrapper approaches adopted were suitable for guiding the choice of recording sites useful for determining the presence of MI. It should be noted however that in this study recording sites have been suggested on their ability to detect disease and such sites may not be optimal for estimating body surface potential distributions.