Effect of Nintendo Wii (TM)-based motor and cognitive training on activities of daily living in patients with Parkinson's disease: A randomised clinical trial

Objectives To investigate the effect of Nintendo Wii (TM)-based motor cognitive training versus balance exercise therapy on activities of daily living in patients with Parkinson's disease. Design Parallel, prospective, single-blind, randomised clinical trial. Setting Brazilian Parkinson Association. Participants Thirty-two patients with Parkinson's disease (Hoehn and Yahr stages 1 and 2). Interventions Fourteen training sessions consisting of 30 minutes of stretching, strengthening and axial mobility exercises, plus 30 minutes of balance training. The control group performed balance exercises without feedback or cognitive stimulation, and the experimental group performed 10 Wii Fit (TM) games. Main outcome measure Section II of the Unified Parkinson's Disease Rating Scale (UPDRS-II). Randomisation Participants were randomised into a control group (n = 16) and an experimental group (n = 16) through blinded drawing of names. Statistical analysis Repeated-measures analysis of variance (RM-ANOVA). Results Both groups showed improvement in the UPDRS-II with assessment effect (RM-ANOVA P < 0.001, observed power = 0.999). There was no difference between the control group and the experimental group before training {8.9 [standard deviation (SD) 2.9] vs 10.1 (SD 3.8)}, after training [7.6 (SD 2.9) vs 8.1 (SD 3.5)] or 60 days after training [8.1 (SD 3.2) vs 8.3 (SD 3.6)]. The mean difference of the whole group between before training and after training was -0.9 (SD 2.3, 95% confidence interval -1.7 to -0.6). Conclusion Patients with Parkinson's disease showed improved performance in activities of daily living after 14 sessions of balance training, with no additional advantages associated with the Wii-based motor and cognitive training. Registered on http://www.clinicaltrials.gov (identifier: NCT01580787). (C) 2012 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

AEROBIC OR RESISTANCE EXERCISE IMPROVES PERFORMANCE IN ACTIVITIES OF DAILY LIVING IN ELDERLY WOMEN

The purpose of this randomized non-controlled study was to determine the effect of an aerobic or resistance exercise protocol on performance of activities of daily living in elderly women. The sample was constituted of 41 apparently healthy elderly women aged 60 to 85 years (x: 65.1 +/- 7.9 years) randomly assigned in resistance exercise (n: 22) or aerobic groups (n: 19). The resistance exercise protocol consisted of three sets of eight to 12 repetitions at 60% of one repetition maximum test for the leg press 45 degrees. The aerobic exercise protocol consisted in cycling in a cycle ergometer during 40 minutes at 60% of reserve heart rate. Both protocols were performed three times per week during five weeks. Activities of daily living were estimated by velocity to stand from sitting to standing position (VSitting), velocity to move from supine to standing position (VSupine), velocity to climb stairs (VCS) and velocity to wear sneakers (VWS). Volunteers of aerobic exercise protocol improved significantly the time to perform VWS (19.1%), while the volunteers of resistance exercise protocol improved the capacity to perform VCS (4.3%) and VSupine (8.9%). These results let us conclude that aerobic as well as resistance exercise protocols induced positive effect on activities of daily living, suggesting that both protocols must be associated for an adequate exercise program to improve the functional capacity of elderly people.

A robotic system to train activities of daily living in a virtual environment

In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.

Theta burst stimulation reduces disability during the activities of daily living in spatial neglect

Left-sided spatial neglect is a common neurological syndrome following right-hemispheric stroke. The presence of spatial neglect is a powerful predictor of poor rehabilitation outcome. In one influential account of spatial neglect, interhemispheric inhibition is impaired and leads to a pathological hyperactivity in the contralesional hemisphere, resulting in a biased attentional allocation towards the right hemifield. Inhibitory transcranial magnetic stimulation can reduce the hyperactivity of the contralesional, intact hemisphere and thereby improve spatial neglect symptoms. However, it is not known whether this improvement is also relevant to the activities of daily living during spontaneous behaviour. The primary aim of the present study was to investigate whether the repeated application of continuous theta burst stimulation trains could ameliorate spatial neglect on a quantitative measure of the activities of daily living during spontaneous behaviour. We applied the Catherine Bergego Scale, a standardized observation questionnaire that can validly and reliably detect the presence and severity of spatial neglect during the activities of daily living. Eight trains of continuous theta burst stimulation were applied over two consecutive days on the contralesional, left posterior parietal cortex in patients suffering from subacute left spatial neglect, in a randomized, double-blind, sham-controlled design, which also included a control group of neglect patients without stimulation. The results showed a 37% improvement in the spontaneous everyday behaviour of the neglect patients after the repeated application of continuous theta burst stimulation. Remarkably, the improvement persisted for at least 3 weeks after stimulation. The amelioration of spatial neglect symptoms in the activities of daily living was also generally accompanied by significantly better performance in the neuropsychological tests. No significant amelioration in symptoms was observed after sham stimulation or in the control group without stimulation. These results provide Class I evidence that continuous theta burst stimulation is a viable add-on therapy in neglect rehabilitation that facilitates recovery of normal everyday behaviour.

Limb apraxia in multiple sclerosis: prevalence and impact on manual dexterity and activities of daily living

To evaluate the prevalence and impact of limb apraxia on manual dexterity and activities of daily living (ADLs) in patients with multiple sclerosis (MS).

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Outcomes after stroke: Basic and instrumental activities of daily living, community reintegration and generic health status

This study describes the discharge destination, basic and instrumental activities of daily living (ADL), community reintegration and generic health status of people after stroke, and explored whether sociodemographic and clinical characteristics were associated with these outcomes. Participants were 51 people, with an initial stroke, admitted to an acute hospital and discharged to the community. Admission and discharge data were obtained by chart review. Follow-up status was determined by telephone interview using the Modified Barthel Index, the Assessment of Living Skills and Resources, the Reintegration to Normal Living Index, and the Short-Form Health Survey (SF-36). At follow up, 57% of participants were independent in basic ADL, 84% had a low risk of experiencing instrumental ADL difficulties, most had few concerns with community reintegration, and SF-36 physical functioning and vitality scores were lower than normative values. At follow up, poorer discharge basic ADL status was associated with poorer instrumental ADL and community reintegration status, and older participants had poorer instrumental ADL, community reintegration and physical functioning. Occupational therapists need to consider these outcomes when planning inpatient and post-discharge intervention for people after stroke.

Recognition of Activities of Daily Living from Topic Model

Research in ubiquitous and pervasive technologies have made it possible to recognise activities of daily living through non-intrusive sensors. The data captured from these sensors are required to be classified using various machine learning or knowledge driven techniques to infer and recognise activities. The process of discovering the activities and activity-object patterns from the sensors tagged to objects as they are used is critical to recognising the activities. In this paper, we propose a topic model process of discovering activities and activity-object patterns from the interactions of low level state-change sensors. We also develop a recognition and segmentation algorithm to recognise activities and recognise activity boundaries. Experimental results we present validates our framework and shows it is comparable to existing approaches.

Abuse and neglect of elderly and independence in instrumental and basic activities of daily living.

Introduction: One of the known risk factors for abuse and neglect of the elderly is the decrease in functional capacity, contributing to self care dependency of instrumental activities of daily living and basic activities of daily living (OMS, 2015). Methods: Cross-sectional study with non probabilistic sample of 333 elderly, performed in a hospital, homes and day centers for the elderly. The data collection protocol included socio-demographic data, Questions to elicit Elder Abuse (Carney, Kahan & Paris, 2003 adap. By Ferreira Alves & Sousa, 2005), scale of instrumental activities of daily living Lawton and Brody and Katz index to assess the level of independence in activities of daily living. Objectives: To evaluate the association between abuse and neglect in the elderly, instrumental activities of daily living and level of independence in activities of daily living. Results: Emotional abuse is significantly correlated with the level of independence in activities of daily living (p = 0.000), older people with less independence tend to have higher levels of emotional abuse. The total abuse is significantly correlated with the levels of independence in activities of daily living (p = 0.002), less independent elderly tend to suffer greater abuse and neglect. There were no statistically significant associations between abuse and neglect and instrumental activities of daily living. Conclusions: The less independent elderly are more vulnerable to situations of abuse and neglect, being more exposed to emotional abuse. These results point to the need for health professionals/ nurses develop prevention interventions, including strategies to support carers and early screening in less independent elderly.

Abuse and neglect of elderly and independence in instrumental and basic activities of daily living

Introduction: One of the known risk factors for abuse and neglect of the elderly is the decrease in functional capacity, contributing to self care dependency of instrumental activities of daily living and basic activities of daily living (OMS, 2015). Methods: Cross-sectional study with non probabilistic sample of 333 elderly, performed in a hospital, homes and day centers for the elderly. The data collection protocol included socio-demographic data, Questions to elicit Elder Abuse (Carney, Kahan & Paris, 2003 adap. By Ferreira Alves & Sousa, 2005), scale of instrumental activities of daily living Lawton and Brody and Katz index to assess the level of independence in activities of daily living. Objectives: To evaluate the association between abuse and neglect in the elderly, instrumental activities of daily living and level of independence in activities of daily living. Results: Emotional abuse is significantly correlated with the level of independence in activities of daily living (p = 0.000), older people with less independence tend to have higher levels of emotional abuse. The total abuse is significantly correlated with the levels of independence in activities of daily living (p = 0.002), less independent elderly tend to suffer greater abuse and neglect. There were no statistically significant associations between abuse and neglect and instrumental activities of daily living. Conclusions: The less independent elderly are more vulnerable to situations of abuse and neglect, being more exposed to emotional abuse. These results point to the need for health professionals/ nurses develop prevention interventions, including strategies to support carers and early screening in less independent elderly.

VALIDATION OF THE LONDON CHEST ACTIVITY OF DAILY LIVING SCALE IN PATIENTS WITH HEART FAILURE

Background: The Minnesota Living with Heart Failure Questionnaire (MLHFQ) is a well-validated, commonly-used tool to assess quality of life in patients with heart failure. However, it lacks specific information concerning breathlessness during daily activities. Objective: To determine the validity of the London Chest Activity of Daily Living (LCADL) scale for use in patients with heart failure. Methods: Forty-seven patients with heart failure (57% males, mean age 50 years (standard deviation 9), mean left ventricle ejection fraction 29% (SD 6), New York Heart Association (NYHA) functional class I-III) were included. All subjects first performed a cardiopulmonary exercise test and then responded to the LCADL and the MLHFQ, with guidance from the same investigator. The re-test for the LCADL was applied one week later. Results: LCADL was correlated with MLHFQ (r=0.88; p < 0.0001). LCADL and MLHFQ were also correlated with exercise capacity (r=-0.75 and r=-0.73, respectively; both p < 0.0001). The LCADL was shown to be reproducible (r(i)=0.98). There was a significant difference (p < 0.05) in the LCADL scores between NYHA functional classes I and II, as well as classes I and III, hut not between classes II and III. Conclusion: The LCADL was shown to be a valid measurement of dyspnoea during daily activities in patients with heart failure. This scale could be an additional useful tool for the assessment of patients` dyspnoea during activities of daily living.