ABSTRACT
BACKGROUND: Early detection of behavioral changes in Alzheimer's disease (AD) would help the design and implementation of specific interventions. OBJECTIVE: The target of our investigation was to establish a correlation between diagnosis and unconstrained motion behavior in subjects without major clinical behavior impairments. METHOD: We studied everyday motion behavior in 23 dyads with one partner suffering from AD dementia and one cognitively healthy partner in the subjects' home, employing ankle-mounted three-axes accelerometric sensors. We determined frequency features obtained from the signal envelopes computed by an envelope detector for the carrier band 0.5 Hz to 5 Hz. Based on these features, we employed quadratic discriminant analysis for building models discriminating between AD patients and healthy controls. RESULTS: After leave-one-out cross-validation, the classification accuracy of motion features reached 91% and was superior to the classification accuracy based on the Cohen-Mansfield Agitation Inventory (CMAI). Motion features were significantly correlated with MMSE and CMAI scores. CONCLUSION: Our findings suggest that changes of everyday behavior are detectable in accelerometric behavior protocols even in the absence of major clinical behavioral impairments in AD.
Subject(s)
Activities of Daily Living , Alzheimer Disease/complications , Behavioral Symptoms/diagnosis , Behavioral Symptoms/etiology , Movement Disorders/diagnosis , Movement Disorders/etiology , Accelerometry , Aged , Aged, 80 and over , Discriminant Analysis , Female , Humans , Male , Mental Status Schedule , Middle Aged , Predictive Value of Tests , ROC Curve , Statistics as TopicABSTRACT
We conducted a pilot trial of electronic technology integrated into the treatment of children and adolescents who are overweight or obese. A total of 30 patients (mean age 14 years, mean BMI 32.7 kg/m(2)) were admitted to our hospital to participate in a structured treatment and teaching programme (STTP). To assess physical activity and eating habits, a mobile motion sensor board (MoSeBo) or a sensor for physical activity, integrated into a mobile phone with digital camera (DiaTrace) was used. Over an average period of four days of monitoring, the mean intensity (15.4 activity units) and duration of physical activity (267 min/d) were recorded with the mobile sensors. The mean time spent walking was 64 min/d, running 11 min/d, cycling 24 min/d and car driving 21 min/d. There were significant differences (P < 0.001) between self-reported physical activity and objective assessment: in general the duration of physical activity documented by children and adolescents was much higher than the objective assessment. Similarly, the real caloric intake was higher than the self-estimates (P = 0.085). A multivariate analysis showed that the following variables were significantly associated with weight reduction in the hospital STTP (R-squared = 0.59): high motivation, intrafamilial conflicts, duration of physical activity assessed with the MoSeBo/DiaTrace system, and the body fat mass at onset of therapy. All children and adolescents included in the trial completed it. Although the MoSeBo/DiaTrace system was used for a relatively short period in each patient, the high acceptance demonstrated that it could be integrated into therapy easily.
