Biological Measurement Triggering via Sensor Data Analysis
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Solution Overview
Problem
Current healthcare systems face challenges in optimizing hospital stays and efficiently managing patient care, leading to resource constraints and increased infection risks due to prolonged hospitalizations, which can be addressed by enabling remote monitoring of patients' biological parameters.
Innovation Solution
A system comprising a memory for storing sensor data and processing cores that determine propitious conditions for biological measurements, triggering signals for measurements, and evaluating the reliability of collected data to ensure accurate and comparable readings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patients are monitored continuously in hospital, then measurement reliability is improved, but loss of time and healthcare resource efficiency deteriorate
Solution Approach 1:
The system performs preliminary assessments using sensor data (movement, posture, heart rate) before triggering a biological measurement to ensure conditions are propitious, thereby preparing the measurement environment in advance to guarantee reliability without requiring continuous hospital monitoring
Solution Approach 2:
The system continuously monitors sensor data and provides feedback to determine when propitious conditions occur, dynamically triggering measurements only when conditions are suitable, thus maintaining measurement reliability while minimizing hospital stay duration
2Measurement precision
If biological measurements are performed frequently, then measurement precision is improved, but device complexity and resource consumption increase
Solution Approach 1:
The system changes the parameters of measurement triggering based on sensor data analysis, switching from fixed-interval measurements to condition-based triggering, thereby maintaining measurement precision while reducing overall measurement frequency and system complexity
Solution Approach 2:
The system performs measurements selectively only when propitious conditions are detected, rather than continuously or at fixed intervals, achieving sufficient measurement precision for healthcare purposes while reducing device complexity and resource consumption
3Productivity
If remote monitoring is implemented, then healthcare efficiency is improved, but measurement reliability may deteriorate due to uncontrolled conditions
Solution Approach 1:
Before performing a biological measurement in a remote setting, the system preliminarily assesses multiple conditions using sensor data (movement, posture, heart rate variability) to ensure the environment is suitable, thereby maintaining measurement reliability while enabling efficient remote monitoring
Solution Approach 2:
The system autonomously determines whether conditions are propitious for measurement and self-regulates the measurement triggering process, eliminating the need for continuous medical supervision while ensuring measurement reliability through automated condition assessment
Data Source
AI summary
According to an example aspect of the present invention, there is provided an apparatus comprising a memory configured to store sensor data obtained from a person, and at least one processing core configured to perform a determination, based at least partly on the stored sensor data, concerning whether conditions are propitious to a biological measurement, and responsive to the conditions being determined to be propitious, to cause a triggering signal to be initiated concerning the biological measurement.