Enhanced Data Visualization: Our dashboard transforms raw sensor data into clear, actionable insights, making it easier for healthcare practitioners to identify trends and patterns.

User-Friendly Interface: Designed with usability in mind, the dashboard features a clean, intuitive interface that simplifies the process of data analysis.

Comprehensive Biomarker Analysis: With 20 biomarker features displayed, practitioners can now monitor and evaluate a wide range of health indicators at a glance.

Group Categorization: Participants are organized into two distinct categories: MCI (Mild Cognitive Impairment) and NON-MCI. This enables a focused analysis of health data based on their key groups.

Flexible Group Selection: Healthcare practitioners can easily select which participant groups to analyze in detail. This flexibility allows for tailored investigations and insights into specific categories.

Enhanced Data Interpretation: By grouping participants and selecting specific groups for detailed analysis, practitioners can more effectively interpret health data and identify significant trends and differences between MCI and NON-MCI participants.

Flexible Selection: Healthcare practitioners / Data Engineers can easily select which participant to analyze in detail. This flexibility allows for tailored investigations and insights into specific categories.

Enhanced Data Interpretation: The filter option allows practitioners to select specific participants for detailed analysis based on age group, gender, and state/area of residence. This enables practitioners to more effectively interpret health data and identify significant trends and differences between participants.

Import/Export Functionality: The system supports importing and exporting participant details to CSV files, enabling offline access to the information.

User-Friendly Interface: It provides the team an overview of the sensors status and the total number of participants involved in the study.  

Sensor Data Interpretation: Monitor sensor health by categorizing battery status into three distinct stages: High, Medium, and Low. This classification helps data engineers to proactively manage sensor performance, ensuring timely maintenance and preventing potential issues that could affect data accuracy.

Precise Sensor Indicator: The low battery status alert enables engineers to take precautionary measures, preventing the battery from falling to zero and minimizing noise in data collection.