Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Timely recognition of cognitive impairment such as Alzheimer’s disease is of great significance. Many smart systems, developed to continuously monitor subjects’ health and cognition, use a number of predefined measures associated with the subjects’ activity in their homes. Hover, this approach has been demonstrated to focus on the idiosyncratic nuances of the individual subjects and thus could potentially not perform as ll on new subjects. ,  address this problem by building proper statistical models of the subjects’ in-home walking speed. Using the data pertaining to 15 older adults monitored for an average period of 3 years,  used linear regression with a Gaussian likelihood to model the in-home walking speed of the subjects, and  used dynamic time warping to demonstrate significant difference beten the walking speed distributions of the subjects when cognitively intact and when suffering from MCI. Using a simple thresholding approach of the dynamic time warping costs,  re able to detect MCI in older adults with an area under the ROC curve and an area under the precision-recall curve of 0.906 and 0.790, respectively, using a time frame of 12 eks.
['Ahmad Akl', 'Alex Mihailidis']
I am writing a research paper on a idea Estimating in-home walking speed distributions for unobtrusive detection of mild cognitive impairment in older adults.
[{"from": "human", "value": "I am writing a research paper on a idea Estimating in-home walking speed distributions for unobtrusive detection of mild cognitive impairment in older adults."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Timely recognition of cognitive impairment such as Alzheimer\u2019s disease is of great significance. Many smart systems, developed to continuously monitor subjects\u2019 health and cognition, use a number of predefined measures associated with the subjects\u2019 activity in their homes. Hover, this approach has been demonstrated to focus on the idiosyncratic nuances of the individual subjects and thus could potentially not perform as ll on new subjects. ,  address this problem by building proper statistical models of the subjects\u2019 in-home walking speed. Using the data pertaining to 15 older adults monitored for an average period of 3 years,  used linear regression with a Gaussian likelihood to model the in-home walking speed of the subjects, and  used dynamic time warping to demonstrate significant difference beten the walking speed distributions of the subjects when cognitively intact and when suffering from MCI. Using a simple thresholding approach of the dynamic time warping costs,  re able to detect MCI in older adults with an area under the ROC curve and an area under the precision-recall curve of 0.906 and 0.790, respectively, using a time frame of 12 eks."}]