Effect of a multimodal exercise program on sleep disturbances and instrumental activities of daily living performance on Parkinson's and Alzheimer's disease patients

Aim: To assess the contribution of a multimodal exercise program on the sleep disturbances (SD) and on the performance of instrumental activities daily living (IADL) in patients with clinical diagnosis of Alzheimer's disease (AD) and Parkinson's disease patients (PD). Methods: A total of 42 consecutive patients (23 training group, 19 control group) with PD and 35 demented patients with AD (19 trained group, 16 control group) were recruited. Participants in both training groups carried out three 1-h sessions per week of a multimodal exercise program for 6 months. The Pfeffer Questionnaire for Instrumental Activities and the Mini-Sleep Questionnaire were used to assess the effects of the program on IADL and SD respectively. Results: Two-way ancova showed interactions in IADL and SD. Significant improvements were observed for these variables in both intervention groups, and maintenance or worsening was observed in control groups. The analysis of effect size showed these improvements. Conclusion: The present study results show that a mild to moderate intensity of multimodal physical exercises carried out on a regular basis over 6 months can contribute to reducing IADL deficits and attenuating SD. © 2013 Japan Geriatrics Society.

Instrumental activities of daily living performance in healthy and cognitively intact seniors from a Brazilian sample and its relation to age and other socio-demographic variables

Background: Studies on functional capacity in community-dwelling older people have shown associations between declines in instrumental activities of daily living (IADL) and several factors. Among these, age has been the most consistently related to functional capacity independent of other variables. We aimed at evaluating the performance of a sample of healthy and cognitively intact Brazilian older people on activities of daily living and to analyze its relation to social-demographic variables. Methods: We conducted a secondary analysis of data collected for previous epidemiological studies with community-dwelling subjects aged 60 years or more. We selected subjects who did not have dementia or depression, and with no history of neurological diseases, heart attack, HIV, hepatitis or arthritis (n = 1,111). Functional capacity was assessed using the Brazilian version of the Older American Resources and Services Questionnaire (BOMFAQ). ADL performance was analyzed according to age, gender, education, and marital status (Pearson's chi(2), logistic regression). Results: IADL difficulties were present in our sample, especially in subjects aged 80 years or more, with lower levels of education, or widowed. The logistic regression analysis results indicated that "higher age" and "lower education" (p <= 0.001) remained significantly associated with IADL difficulty. Conclusions: Functional decline was present in older subjects even in the absence of medical conditions and cognitive impairment. Clinicians and researchers could benefit from knowing what to expect from older people regarding IADL performance in the absence of medical conditions.

Gender differences in incidence and determinants of disability in activities of daily living among elderly individuals: SABE study

Determining the groups that are most susceptible to developing disability is essential to establishing effective prevention and rehabilitation strategies. The aim of the present study was to determine gender differences in the incidence of disability regarding activities of daily living (ADL) and determinants among elderly residents of Sao Paulo, Brazil. In 2000, 1634 elderly with no difficulties regarding ADL (modified Katz Index) were selected. These activities were reassessed in 2006 and disability was the outcome for the analysis of determinants. The following characteristics were analyzed at baseline: sociodemographic, behavioral, health status, medications, falls, hospitalizations, depressive symptoms, cognition, handgrip, mobility and balance. The incidence density was 42.4/1000 women/year and 17.5/1000 men/year. After adjusting for socioeconomic status and health conditions, women with chronic diseases and social vulnerability continued to have a greater incidence of disability. The following were determinants of the incidence of disability: age and depressive symptoms in both genders; stroke and slowness on the sit-and-stand test among men; and osteoarthritis and sedentary lifestyle among women. Better cognitive performance and handgrip strength were protective factors among men and women, respectively. Adverse clinical and social conditions determine differences between genders regarding the incidence of disability. Decreased mobility and balance and health conditions that affect the central nervous system or lead to impaired cognition disable men more, whereas a sedentary lifestyle, reduction in muscle strength and conditions that affect the osteoarticular system disable women more. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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).

Ecological validity of virtual reality daily living activities screening for early dementia: longitudinal study

Background: Dementia is a multifaceted disorder that impairs cognitive functions, such as memory, language, and executive functions necessary to plan, organize, and prioritize tasks required for goal-directed behaviors. In most cases, individuals with dementia experience difficulties interacting with physical and social environments. The purpose of this study was to establish ecological validity and initial construct validity of a fire evacuation Virtual Reality Day-Out Task (VR-DOT) environment based on performance profiles as a screening tool for early dementia. Objective: The objectives were (1) to examine the relationships among the performances of 3 groups of participants in the VR-DOT and traditional neuropsychological tests employed to assess executive functions, and (2) to compare the performance of participants with mild Alzheimer’s-type dementia (AD) to those with amnestic single-domain mild cognitive impairment (MCI) and healthy controls in the VR-DOT and traditional neuropsychological tests used to assess executive functions. We hypothesized that the 2 cognitively impaired groups would have distinct performance profiles and show significantly impaired independent functioning in ADL compared to the healthy controls. Methods: The study population included 3 groups: 72 healthy control elderly participants, 65 amnestic MCI participants, and 68 mild AD participants. A natural user interface framework based on a fire evacuation VR-DOT environment was used for assessing physical and cognitive abilities of seniors over 3 years. VR-DOT focuses on the subtle errors and patterns in performing everyday activities and has the advantage of not depending on a subjective rating of an individual person. We further assessed functional capacity by both neuropsychological tests (including measures of attention, memory, working memory, executive functions, language, and depression). We also evaluated performance in finger tapping, grip strength, stride length, gait speed, and chair stands separately and while performing VR-DOTs in order to correlate performance in these measures with VR-DOTs because performance while navigating a virtual environment is a valid and reliable indicator of cognitive decline in elderly persons. Results: The mild AD group was more impaired than the amnestic MCI group, and both were more impaired than healthy controls. The novel VR-DOT functional index correlated strongly with standard cognitive and functional measurements, such as mini-mental state examination (MMSE; rho=0.26, P=.01) and Bristol Activities of Daily Living (ADL) scale scores (rho=0.32, P=.001). Conclusions: Functional impairment is a defining characteristic of predementia and is partly dependent on the degree of cognitive impairment. The novel virtual reality measures of functional ability seem more sensitive to functional impairment than qualitative measures in predementia, thus accurately differentiating from healthy controls. We conclude that VR-DOT is an effective tool for discriminating predementia and mild AD from controls by detecting differences in terms of errors, omissions, and perseverations while measuring ADL functional ability.

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.

Passive wireless sensor systems can recognize activites of daily living

The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.