Exploring Patterns of Activities of Daily Living in the Home Environment

Background: Senior citizens tend to live longer and longer independently. Judging whether a senior person is still capable of living on his own is often based on the occurrence of incidents, with all consequences thereof. In the specific case of early dementia, the symptoms are not immediately apparent and the occurrence and severity of incidents progress gradually over time. In this case, the children or grandchildren are burdened by the question whether or not the elderly adult can still live safely and independently in his or her own home. This decision is only based on input obtained through incidental visits. We believe that the capability of independent living can only be objectively judged, by a health professional, if long term objective information on the elderly person's daily activities of living (ADL) is available

Boxed In: The True Cost of Extreme Isolation in New York's Prisons

The NYCLU set out to investigate New York's use of extreme isolation. We explored the history that led to the emergence and expansion of the practice in New York. We asked who New York subjects to extreme isolation, for what reasons, and for how long. We sought to understand and articulate its effects on prisoners and their families, as well as an often-overlooked population -- the corrections staff assigned to watch them. We compared New York's use of extreme isolation with practices in other states and asked if the widespread use of the practice violates legal standards. Finally, we considered how reforming the use of extreme isolation would affect the safety of New York's prisons and communities.In order to answer these questions, the NYCLU conducted an intensive year-long investigation. We communicated with more than 100 prisoners who have spent significant amounts of time -- in one case, more than 20 years -- inside a SHU cell. We interviewed family members and corrections staff. We consulted corrections experts, mental health professionals, lawyers and academics. We read decades of DOCCS reports and press coverage recounting the history of New York's SHU expansion. We researched the scientific and academic literature regarding the use and effects of extreme isolation. We studied domestic and international legal standards governing extreme isolation and the steps undertaken by other states to reform their use of the practice. Finally, we reviewed DOCCS' internal regulations and policies and analyzed thousands of pages of official DOCCS records obtained through New York's open records laws

Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Solitary living in Alzheimer's disease over 3 years: association between cognitive and functional impairment and community-based services.

Introduction: Many individuals with Alzheimer’s disease (AD) live alone, and this figure is expected to increase. This study aimed to describe the cognitive and functional abilities of solitary-living AD patients, and the potential predictors of their usage of community-based services. Methods: This 3-year, prospective, multicenter study included 1,021 participants with mild-to-moderate AD (Mini-Mental State Examination score, 10–26) treated with cholinesterase inhibitors (ChEI) in a routine clinical setting. At the baseline and every 6 months, patients were assessed using cognitive, instrumental and basic activities of daily living (ADL) scales, and service utilization was recorded. Logistic regression models were used to predict the usage of community-based services. Results: At the start of ChEI therapy (time of AD diagnosis), 355 individuals (35%) were living alone. They were mainly female, older, had more impaired basic ADL capacity, and a larger number of concomitant medications compared with those living with family. Regarding the solitary-living patients, lower instrumental ADL (IADL) ability and more medications were independent predictors of usage of home-help services, whereas more impaired IADL at baseline and faster IADL deterioration were predictors of nursing-home admission. For those living with family, older age, lower basic ADL, and a greater number of medications predicted home-help services, whereas a larger amount of home help predicted nursing-home placement. In addition, female sex was a risk factor for both the utilization of home-help services and nursing-home placement. Cognitive ability was not significantly associated with usage of community-based services. Conclusions: A large number of AD patients, predominantly females, live alone with severe cognitive and functional impairment. The amount of home-help services used did not reflect cognitive severity, suggesting that home help did not meet the needs related to cognitive deterioration. Increased knowledge of how community-based services can better accommodate the care needs of solitary-living individuals with AD is essential

Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly

Mobile electrocardiogram (ECG) monitoring is an emerging area that has received increasing attention in recent years, but still real-life validation for elderly residing in low and middle-income countries is scarce. We developed a wearable ECG monitor that is integrated with a self-designed wireless sensor for ECG signal acquisition. It is used with a native purposely designed smartphone application, based on machine learning techniques, for automated classification of captured ECG beats from aged people. When tested on 100 older adults, the monitoring system discriminated normal and abnormal ECG signals with a high degree of accuracy (97%), sensitivity (100%), and specificity (96.6%). With further verification, the system could be useful for detecting cardiac abnormalities in the home environment and contribute to prevention, early diagnosis, and effective treatment of cardiovascular diseases, while keeping costs down and increasing access to healthcare services for older persons

Probabilistic Analysis of Temporal and Sequential Aspects of Activities of Daily Living for Abnormal Behaviour Detection

This paper presents a probabilistic approach for the identification of abnormal behaviour in Activities of Daily Living (ADLs) from dense sensor data collected from 30 participants. The ADLs considered are related to preparing and drinking (i) tea, and (ii) coffee. Abnormal behaviour identified in the context of these activities can be an indicator of a progressive health problem or the occurrence of a hazardous incident. The approach presented considers the temporal and sequential aspects of the actions that are part of each ADL and that vary between participants. The average and standard deviation for the duration and number of steps of each activity are calculated to define the average time and steps and a range within which a behaviour could be considered as normal for each stage and activity. The Cumulative Distribution Function (CDF) is used to obtain the probabilities of abnormal behaviours related to the early and late completion of activities and stages within an activity in terms of time and steps. Analysis shows that CDF can provide precise and reliable results regarding the presence of abnormal behaviour in stages and activities that last over a minute or consist of many steps. Finally, this approach could be used to train machine learning algorithms for abnormal behaviour detection.status: publishe