A therapy dog's impact on daytime activity and night-time sleep for older persons with Alzheimer's disease : a case study

Background: Animal-Assisted Therapy using dogs have been described as having a calming effect, decrease sundowning and blood-pressure in persons with Alzheimer’s disease. The aim was to investigate how continuous and scheduled visits by a prescribed therapy dog affected daytime and night-time sleep for persons with Alzheimer’s disease. Methods: In this case study, registration of activity and sleep curves was conducted from five persons with moderate to severe Alzheimer’s disease living at a nursing home, over a period of 16 weeks using an Actiwatch. Data was analysed with descriptive statistics. Result: The study shows no clear pattern of effect on individual persons daytime activity and sleep when encounter with a therapy dog, but instead points to a great variety of possible different effects that brings an increased activity at different time points, for example during night-time sleep. Conclusions: Effects from the use of a Animal-Assisted Therapy with a dog in the care of persons with Alzheimer’s disease needs to be further investigated and analysed from a personcentred view including both daytime and nightime activities.

Can therapy dogs evoke awareness of one's past and present life in persons with Alzheimer's disease?

BACKGROUND: Persons with Alzheimer's disease (AD) sometimes express themselves through behaviours that are difficult to manage for themselves and their caregivers, and to minimise these symptoms alternative methods are recommended. For some time now, animals have been introduced in different ways into the environment of persons with dementia. Animal-Assisted Therapy (AAT) includes prescribed therapy dogs visiting the person with dementia for a specific purpose. AIM: This study aims to illuminate the meaning of the lived experience of encounters with a therapy dog for persons with Alzheimer's disease. METHOD: Video recorded sessions were conducted for each visit of the dog and its handler to a person with AD (10 times/person). The observations have a life-world approach and were transcribed and analysed using a phenomenological hermeneutical approach. RESULTS: The result shows a main theme 'Being aware of one's past and present existence', meaning to connect with one's senses and memories and to reflect upon these with the dog. The time spent with the dog shows the person recounting memories and feelings, and enables an opportunity to reach the person on a cognitive level. CONCLUSIONS: The present study may contribute to health care research and provide knowledge about the use of trained therapy dogs in the care of older persons with AD in a way that might increase quality of life and well-being in persons with dementia. IMPLICATIONS FOR PRACTICE: The study might be useful for caregivers and dog handlers in the care of older persons with dementia.

Unsupervised learning to cluster the disease stages in parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's disease) and directly affects upto 5 million people worldwide. The stages (Hoehn and Yaar) of disease has been predicted by many methods which will be helpful for the doctors to give the dosage according to it. So these methods were brought up based on the data set which includes about seventy patients at nine clinics in Sweden. The purpose of the work is to analyze unsupervised technique with supervised neural network techniques in order to make sure the collected data sets are reliable to make decisions. The data which is available was preprocessed before calculating the features of it. One of the complex and efficient feature called wavelets has been calculated to present the data set to the network. The dimension of the final feature set has been reduced using principle component analysis. For unsupervised learning k-means gives the closer result around 76% while comparing with supervised techniques. Back propagation and J4 has been used as supervised model to classify the stages of Parkinson's disease where back propagation gives the variance percentage of 76-82%. The results of both these models have been analyzed. This proves that the data which are collected are reliable to predict the disease stages in Parkinson's disease.