Data Mining - Concepts and Techniques.

OBJECTIVE — To systematically review the incidence of posttransplantation diabetes (PTD), risk factors for its development, prognostic implications, and optimal management. RESEARCH DESIGN AND METHODS — We searched databases (MEDLINE, EMBASE, the Cochrane Library, and others) from inception to September 2000, reviewed bibliographies in reports retrieved, contacted transplantation experts, and reviewed specialty journals. Two reviewers independently determined report inclusion (original studies, in all languages, of PTD in adults with no history of diabetes before transplantation), assessed study methods, and extracted data using a standardized form. Meta-regression was used to explain between-study differences in incidence. RESULTS — Nineteen studies with 3,611 patients were included. The 12-month cumulative incidence of PTD is lower (10% in most studies) than it was 3 decades ago. The type of immunosuppression explained 74% of the variability in incidence (P 0.0004). Risk factors were patient age, nonwhite ethnicity, glucocorticoid treatment for rejection, and immunosuppression with high-dose cyclosporine and tacrolimus. PTD was associated with decreased graft and patient survival in earlier studies; later studies showed improved outcomes. Randomized trials of treatment regimens have not been conducted. CONCLUSIONS — Physicians should consider modification of immunosuppressive regimens to decrease the risk of PTD in high-risk transplant recipients. Randomized trials are needed to evaluate the use of oral glucose-lowering agents in transplant recipients, paying particular attention to interactions with immunosuppressive drugs. Diabetes Care 25:583–592, 2002

A systematic review of the literature

The dielectric properties of tissues have been extracted from the literature of the past five decades and presented in a graphical format. The purpose is to assess the current state of knowledge, expose the gaps there are and provide a basis for the evaluation and analysis of corresponding data from an on-going measurement programme.

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The dielectric properties of biological tissues: I. Literature survey

Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchronous changes in the blood volume with each heart beat, and is superimposed on a slowly varying ('DC') baseline with various lower frequency components attributed to respiration, sympathetic nervous system activity and thermoregulation. Although the origins of the components of the PPG signal are not fully understood, it is generally accepted that they can provide valuable information about the cardiovascular system. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular disease. The introductory sections of the topical review describe the basic principle of operation and interaction of light with tissue, early and recent history of PPG, instrumentation, measurement protocol, and pulse wave analysis. The review then focuses on the applications of PPG in clinical physiological measurements, including clinical physiological monitoring, vascular assessment and autonomic function.

https://iopscience.iop.org/article/10.1088/0967-3334/28/3/R01/pdf

Photoplethysmography and its application in clinical physiological measurement.

Background: About a third of home-dwelling older people fall each year, and institutionalized older people even report a two- or threefold higher rate for falling

Sensitivity and false alarm rate of a fall sensor in long-term fall detection in the elderly

Photoplethysmography (PPG) technology has been used to develop small, wearable, pulse rate sensors. These devices, consisting of infrared light-emitting diodes (LEDs) and photodetectors, offer a simple, reliable, low-cost means of monitoring the pulse rate noninvasively. Recent advances in optical technology have facilitated the use of high-intensity green LEDs for PPG, increasing the adoption of this measurement technique. In this review, we briefly present the history of PPG and recent developments in wearable pulse rate sensors with green LEDs. The application of wearable pulse rate monitors is discussed.

Wearable Photoplethysmographic Sensors—Past and Present

Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique

Objective An entertainment robot was used as occupational therapy instead of animal-assisted therapy to avoid any danger or injury to the patient and maintain cleanliness. This study compared the effectiveness of a robot animal, AIBO, with a toy. Method AIBO is made of metal and responds to spoken commands. We demonstrated AIBO to severely demented elderly people living in a geriatric home and observed their reactions. Results The most frequent reactions to AIBO consisted of looking at, communicating with, and caring for AIBO. The patients recognized that AIBO was a robot. However, once we dressed AIBO, the patients perceived AIBO as either a dog or a baby. Nevertheless, the presentation of AIBO resulted in positive outcomes for the severe dementia patients, including increased communication between the patients and AIBO. Conclusion AIBO was clearly an effective rehabilitation tool in the treatment of severely demented patients.

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Is an entertainment robot useful in the care of elderly people with severe dementia

In this paper, we attempted to classify the acceleration signals for walking along a corridor and on stairs by using the wavelet-based fractal analysis method. In addition, the wavelet-based fractal analysis method was used to evaluate the gait of elderly subjects and patients with Parkinson's disease. The triaxial acceleration signals were measured close to the center of gravity of the body while the subject walked along a corridor and up and down stairs continuously. Signal measurements were recorded from 10 healthy young subjects and 11 elderly subjects. For comparison, two patients with Parkinson's disease participated in the level walking. The acceleration signal in each direction was decomposed to seven detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 7 to 1 were calculated. The fractal dimension of the acceleration signal was then estimated from the slope of the variance progression. The fractal dimensions were significantly different among the three types of walking for individual subjects (p < 0.01) and showed a high reproducibility. Our results suggest that the fractal dimensions are effective for classifying the walking types. Moreover, the fractal dimensions were significantly higher for the elderly subjects than for the young subjects (p < 0.01). For the patients with Parkinson's disease, the fractal dimensions tended to be higher than those of healthy subjects. These results suggest that the acceleration signals change into a more complex pattern with aging and with Parkinson's disease, and the fractal dimension can be used to evaluate the gait of elderly subjects and patients with Parkinson's disease.

Discrimination of walking patterns using wavelet-based fractal analysis

Diabetes mellitus is a heterogeneous clinical syndrome characterized by hyperglycaemia and the long-term complications are retinopathy, neuropathy, nephropathy, and cardiomyopathy. It is a leading cause of blindness. Diabetic retinopathy is the progressive pathological alterations in the retinal microvasculature, leading to areas of retinal nonperfusion, increased vascular permeability, and the pathological proliferation of retinal vessels. Hence, it is beneficial to have regular cost-effective eye screening for diabetes subjects. Nowadays, different stages of diabetes retinopathy are detected by retinal examination using indirect biomicroscopy by senior ophthalmologists. In this work, morphological image processing and support vector machine (SVM) techniques were used for the automatic diagnosis of eye health. In this study, 331 fundus images were analysed. Five groups were identified: normal retina, mild non-proliferative diabetic retinopathy, moderate non-proliferative diabetic retinopathy, severe non-proliferative diabetic retinopathy, and proliferative diabetic retinopathy. Four salient features blood vessels, microaneurysms, exudates, and haemorrhages were extracted from the raw images using image-processing techniques and fed to the SVM for classification. A sensitivity of more than 82 per cent and specificity of 86 per cent was demonstrated for the system developed.

Toshiyo Tamura

Papers

Wearable Photoplethysmographic Sensors—Past and Present

Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique

Is an entertainment robot useful in the care of elderly people with severe dementia

Discrimination of walking patterns using wavelet-based fractal analysis

Computer-based detection of diabetes retinopathy stages using digital fundus images.