Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and ll-being assessment. ,  examine the actual benefits of smart home-based analysis by monitoring daily behavior in the home and predicting clinical scores of the residents. To accomplish this goal,  propose a clinical assessment using activity behavior (CAAB) approach to model a smart home resident's daily behavior and predict the corresponding clinical scores. CAAB uses statistical features that describe characteristics of a resident's daily activity performance to train machine learning algorithms that predict the clinical scores.  evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years.  obtain a statistically significant correlation ( r=0.72) beten CAAB-predicted and clinician-provided cognitive scores and a statistically significant correlation ( r=0.45) beten CAAB-predicted and clinician-provided mobility scores. These prediction results suggest that it is feasible to predict clinical scores using smart home sensor data and learning-based data analysis.
['Prafulla N. Dawadi', 'Diane J. Cook', 'Maureen Schmitter-Edgecombe']
I am writing a research paper on a idea Automated Cognitive Health Assessment From Smart Home-Based Behavior Data
[{"from": "human", "value": "I am writing a research paper on a idea Automated Cognitive Health Assessment From Smart Home-Based Behavior Data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and ll-being assessment. ,  examine the actual benefits of smart home-based analysis by monitoring daily behavior in the home and predicting clinical scores of the residents. To accomplish this goal,  propose a clinical assessment using activity behavior (CAAB) approach to model a smart home resident's daily behavior and predict the corresponding clinical scores. CAAB uses statistical features that describe characteristics of a resident's daily activity performance to train machine learning algorithms that predict the clinical scores.  evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years.  obtain a statistically significant correlation ( r=0.72) beten CAAB-predicted and clinician-provided cognitive scores and a statistically significant correlation ( r=0.45) beten CAAB-predicted and clinician-provided mobility scores. These prediction results suggest that it is feasible to predict clinical scores using smart home sensor data and learning-based data analysis."}]