Biological Signal Quality Selection Using Cross-Device Time Alignment
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Solution Overview
Problem
Existing systems fail to precisely synchronize data from multiple medical devices due to network latencies and clock inconsistencies, leading to misaligned waveform data that reduces the effectiveness of analysis and detection of health-related events.
Innovation Solution
A method for synchronizing waveform data from multiple devices by assigning sequence numbers, unwrapping them to correct for network transmission delays, and calculating adjusted timestamps to align data accurately within milliseconds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is transmitted over networks from multiple medical devices, then data collection capability is improved, but time synchronization precision deteriorates due to network latencies
Solution Approach 1:
The system performs preliminary time stamping at the source device before network transmission. Each data packet is assigned a precise time stamp by the generating device's clock, allowing the original timing information to be preserved and reconstructed even after network latency variations
Solution Approach 2:
A centralized server acts as an intermediary that collects time stamped data from multiple devices and performs post-processing synchronization. The server calculates time offsets between devices based on their time stamped data and reconstructs synchronized waveforms by compensating for transmission delays
2Measurement precision
If high-precision atomic clocks are used for synchronization, then time synchronization precision is improved, but device complexity and cost increase
Solution Approach 1:
The system replaces expensive atomic clocks with inexpensive standard device clocks. Each medical device uses its own built-in clock for time stamping, and the system accepts that these clocks may drift slightly. The synchronization is achieved through software-based time offset calculation and waveform reconstruction rather than hardware-based precise clock synchronization
Solution Approach 2:
The system replaces hardware-based time synchronization mechanisms (atomic clocks, precision timing circuits) with software-based time stamping and post-processing algorithms. The synchronization is achieved through computational methods including time offset calculation, waveform interpolation, and temporal alignment algorithms
3Measurement precision
If waveform data is synchronized to within milliseconds, then analysis accuracy is improved, but data processing complexity increases
Solution Approach 1:
Time stamping is performed preliminarily at the source device for each data packet before transmission. This preserves the original timing information, allowing the receiving system to reconstruct synchronized waveforms without needing to perform complex real-time synchronization processing
Solution Approach 2:
The system calculates time offsets between devices based on their time stamped data and uses this feedback to adjust and align waveforms from different devices. The time offset information is used to compensate for transmission delays and clock drift, achieving millisecond-level synchronization
Data Source
AI summary
A method that selects high-quality data within recorded signals from patient monitoring devices, where portions of the signals may be corrupted by noise and should therefore be excluded. Signals are compared to models of expected signal characteristics, and portions of the signals that do not match the models may be excluded. Some models may check for expected relationships between signals from different devices. One such model identifies feature points in two signals from two different devices and calculates the time difference between each feature point in one signal and the earliest subsequent feature point in the other signal; data is excluded if this time difference exceeds an expected range. For example, an expected relationship between electrocardiogram and blood pressure signals is that the R-wave peak should be followed by a blood pressure peak within an expected delay time (the pulse transit time); this check can exclude invalid ECG/BP data.