Background: There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. Methods: We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. Results: The CSHA Clinical Frailty Scale was highly correlated ( r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%–30.6%) and entry into an institution (23.9%, 95% CI 8.8%–41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Interpretation: Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.

/pdf/a-global-clinical-measure-of-fitness-and-frailty-in-elderly-17k380brym.pdf

A global clinical measure of fitness and frailty in elderly people

Thank you for downloading an introduction to the event related potential technique. Maybe you have knowledge that, people have look hundreds times for their favorite readings like this an introduction to the event related potential technique, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious bugs inside their laptop.

An Introduction To The Event Related Potential Technique

Principles and Practice of Sleep Medicine

A smart home is an application of ubiquitous computing in which the home environment is monitored by ambient intelligence to provide context-aware services and facilitate remote home control. This paper presents an overview of previous smart home research as well as the associated technologies. A brief discussion on the building blocks of smart homes and their interrelationships is presented. It describes collective information about sensors, multimedia devices, communication protocols, and systems, which are widely used in smart home implementation. Special algorithms from different fields and their significance are explained according to their scope of use in smart homes. This paper also presents a concrete guideline for future researchers to follow in developing a practical and sustainable smart home.

A Review of Smart Homes—Past, Present, and Future

Many people living with chronic conditions have multiple chronic conditions. Multimorbidity is defined here as the co-existence of two or more chronic conditions, where one is not necessarily more central than the others. Multimorbidity affects quality of life, ability to work and employability, disability and mortality. Currently, clinicians have limited guidance or evidence as to how to approach care decisions for such patients. Understanding how to best care and design the health system for patients with multimorbidity may lead to improvements in quality of life, utilization of healthcare, safety, morbidity and mortality. The objective of this paper is to review the implications of multimorbidity for the design of health system and to understand the research needs for this population. The consideration of people with multimorbidity is essential in the design and evaluation of health systems. Fundamentally, people with multimorbidity should receive a patient — and family-centered approach to care throughout the health system, and understanding how to deliver this type of care in effective and efficient ways is an enormous challenge, and opportunity, for clinicians, researchers, and policy makers today.

/pdf/future-of-multimorbidity-research-how-should-understanding-2sig3qsmzy.pdf

Future of multimorbidity research: how should understanding of multimorbidity inform health system design?

https://www.archives-pmr.org/article/S0003-9993(02)04929-8/pdf

State of the art in geriatric rehabilitation. Part I: review of frailty and comprehensive geriatric assessment.

Among older adults, the challenges of maintaining mobility and cognitive function make it increasingly difficult to remain living alone independently. As a result, many older adults are forced to seek residence in costly clinical institutions where they can receive constant medical supervision. A home-based automated system that monitors their health and well- being while remaining unobtrusive would provide them with a more comfortable and independent lifestyle, as well as more affordable care. This paper presents a smart home system for the elderly, developed by the Technology Assisted Friendly Environment for the Third Age (TAFETA) group. It introduces the sensor technologies integrated in the system and develops a framework for the processing and communication of the extracted information. It also considers the acceptability and implications of this technology from the perspective of the potential occupants.

Integration of Smart Home Technologies in a Health Monitoring System for the Elderly

OBJECTIVES: To measure and describe medical comorbidity in geriatric rehabilitation patients and investigate its relationship to rehabilitation efficiency. DESIGN: Prospective, multivariate, within-subject design. SETTING: The Geriatric Rehabilitation inpatient unit of the SCO Health Service in Ottawa, Canada. PARTICIPANTS: One hundred ten patients, with a mean age of 82 years. MEASUREMENTS: The rehabilitation efficiency ratio, based on gains in functional status achieved with rehabilitation treatment, and the length of stay were computed for all patients. Values were regressed on the scores of the Cumulative Illness Rating Scale (CIRS), the Mini-Mental State Examination, and the Geriatric Depression Scale to establish predictive power. RESULTS: The findings suggest that geriatric rehabilitation patients experience considerable medical comorbidity. Sixty percent of patients had impairments across six of the 13 dimensions of the CIRS, whereas 36% of patients had impairments across 11 of the 13 dimensions. In addition, medical comorbidity was negatively related to rehabilitation efficiency. This relationship was significant even after controlling for age, cognitive status, depressive symptoms, and functional independence status at admission. CONCLUSION: Medical comorbidity was a significant predictor of rehabilitation efficiency in geriatric patients. Comorbidity scores > 5 were prognostic of poorer rehabilitation outcomes and can serve as an empirical guide in estimating a patient's suitability for rehabilitation. Medical comorbidity predicted both the overall functional change achieved with rehabilitation (Functional Independence Measure gains) and the rate at with which those gains were reached (rehabilitation efficiency ratio).

Medical Comorbidity and Rehabilitation Efficiency in Geriatric Inpatients

Smart homes are proposed as a new location for the delivery of healthcare services. They provide healthcare monitoring and communication services, by using integrated sensor network technologies. We validate a hypothesis regarding older adults' adoption of home monitoring technologies by conducting a literature review of articles studying older adults' attitudes and perceptions of sensor technologies. Using current literature to support the hypothesis, this paper applies the tradeoff model to decisions about sensor acceptance. Older adults are willing to trade privacy (by accepting a monitoring technology), for autonomy. As the information captured by the sensor becomes more intrusive and the infringement on privacy increases, sensors are accepted if the loss in privacy is traded for autonomy. Even video cameras, the most intrusive sensor type were accepted in exchange for the height of autonomy which is to remain in the home.

Privacy versus autonomy: A tradeoff model for smart home monitoring technologies

Differentiating dry and wet cough is an important factor in respiratory disease. The main objective of this paper is to analyze cough sounds and extract features that can be used in differentiation of dry and wet cough sounds. This paper proposes two features to achieve this goal. The first feature is the number of peaks of the energy envelope of the cough signal. The second feature is the power ratio of two frequency bands of the second phase of the cough signal. A set of eight highly dry and eight highly wet cough sound recordings were used. Using these two features, a clear separation was observed among the dry and wet cough sound recordings.

https://curve.carleton.ca/system/files/etd/91d9768a-fdfc-4145-a9a4-a2255cdee360/etd_pdf/0ab37fbde60f27301616e43085ba99fb/chatrzarrin-featureextractionforthedifferentiationofdry.pdf

Frank Knoefel

Papers

State of the art in geriatric rehabilitation. Part I: review of frailty and comprehensive geriatric assessment.

Integration of Smart Home Technologies in a Health Monitoring System for the Elderly

Medical Comorbidity and Rehabilitation Efficiency in Geriatric Inpatients

Privacy versus autonomy: A tradeoff model for smart home monitoring technologies

Feature extraction for the differentiation of dry and wet cough sounds