Actigraphy Signal Segmentation for Low-Power Real-Time Compression
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Solution Overview
Problem
Existing wearable devices face challenges in efficiently compressing and segmenting real-time actigraphy data due to high power and memory usage, which limits their capability for long-term monitoring and data recording.
Innovation Solution
A method and system that utilize an accelerometer-based wearable device to encode actigraphy signals using an m-bit encoder, calculate a rapid change factor, and automatically define segment boundaries to extract frames of interest, thereby reducing data transmission and storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional signal sampling and quantization techniques are used, then data acquisition is achieved, but power and memory usage increase significantly
Solution Approach 1:
The patent segments the actigraphy signal into multiple frames and processes each frame independently through difference calculation. By dividing the continuous signal into discrete segments and only transmitting segments with significant changes (above threshold), the system reduces overall power consumption while maintaining measurement precision for relevant events.
Solution Approach 2:
The patent transforms the actigraphy signal by calculating first and second order differences, changing the parameter representation from raw acceleration values to rate-of-change metrics. This parameter transformation enables more efficient compression and reduces the data volume that requires power-intensive transmission and storage.
2Loss of information
If conventional signal processing methods are used, then complete actigraphy data is captured, but memory usage increases
Solution Approach 1:
The patent extracts only the essential features from the actigraphy signal by calculating difference values and comparing them against thresholds. By taking out only the significant movement events (those exceeding the threshold) and discarding redundant static or slowly varying portions, the system preserves important movement information while dramatically reducing memory requirements.
Solution Approach 2:
The patent discards outlying regions of the second order difference signal that fall below the threshold, eliminating redundant data that consumes memory. The system recovers the essential information by reconstructing the actigraphy signal from the remaining significant segments, maintaining measurement completeness for meaningful events while reducing overall data volume.
3Measurement precision
If high sampling rate is used, then signal resolution is improved, but bit-rate increases
Solution Approach 1:
The patent performs preliminary processing of the actigraphy signal by calculating first and second order differences before transmission. This preliminary action of transforming the signal into a compressed difference representation reduces the bit-rate required for transmission while preserving the resolution needed to detect significant movement events, as the difference calculation inherently filters out redundant information.
4Reliability
If conventional filtering techniques are used, then noise is reduced, but computational overhead increases
Solution Approach 1:
The patent replaces complex conventional filtering techniques with a simpler threshold-based difference calculation approach. Instead of using computationally intensive digital filters, the system substitutes a mechanical-like operation of comparing difference values against a threshold, achieving noise reduction and signal quality improvement with significantly reduced computational overhead suitable for low-powered wearable devices.
Data Source
AI summary
There is provided a system, method and device for dynamically compressing an actigraphy signal at a source device. The method comprises receiving the actigraphy signal related to a user's physical activity from an accelerometer sensor on the source device and for compressing the actigraphy signal by determining regions of interest in the actigraphy signal to capture, said compressing performed by: computing a rapid change factor value indicating a drastic change in movement activity in said actigraphy signal, said rapid change factor computed based on determining a spurious free dynamic range of a second order difference signal of the actigraphy signal and subsequently determining the step size of the actigraphy signal, the step size indicating the interval with which the actigraphy signal instantaneously changes its value from one sample to another; automatically scanning the second order difference signal to locate samples in the second order difference signal having a value greater than the rapid change factor value, said located samples defining primary segment boundaries; -extracting frames of the encoded actigraphy signal between two consecutive primary segment boundaries and discarding outlying regions of the encoded actigraphy signal; and —outputting only the extracted frames representing a compressed actigraphy signal to an external computing device for subsequent processing.