Data Models
The SINEW 15 Biomarker dataset was extracted from the sensor data collected by a longitudinal study called Sensors IN-home for Elder Wellbeing (SINEW).
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The SINEW (Sensors in Home for Elderly Wellbeing) dataset consists of 15 high-level biomarker features, derived from raw sensor readings collected by in-home sensors used for predictive modeling research: SINEW Weekly Biomarker.
This dataset was collected for a study focused on the early detection of mild cognitive impairment, providing an opportunity for timely intervention before it progresses to Alzheimer's disease.
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The SINEW (Sensors in Home for Elderly Wellbeing) dataset consists of 15 high-level biomarker features, derived from raw sensor readings collected by in-home sensors used for predictive modeling research: SINEW 15 - Monthly Biomarker.
This dataset was collected for a study focused on the early detection of mild cognitive impairment, providing an opportunity for timely intervention before it progresses to Alzheimer's disease.
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This database is from a family of studies about the user-perceived quality and functional suitability of DEMO's Process and Fact Models. It includes three different samples. Sample 1 consists of the results from a group of professionals within the urban appraisal area. Sample 2 consists of the results from a group of health professionals. Finally, Sample 3 includes the results from a group of students trained in the DEMO standard.
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These datasets contain the whitened data of the COST2100 channel model and consist of eight XLSX files namely: Indo_BI_LOS_Sing_white, Indo_B2_LOS_Sing_white, SemiUr_B1_LOS_Mult_white, SemiUr_B1_LOS_Sing_white, SemiUr_B1_NLOS_Sing_white, SemiUr_B2_LOS_Mult_white, SemiUr_B2_LOS_Sing_white, and SemiUr_B2_NLOS_Sing_white. Each XLSX file consists of 30 sheets. All the sheets contain different number of rows but the same number of columns.
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