MEMS Accelerometer Step Detection Using Correlation and Periodicity Checks
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Solution Overview
Problem
Existing pedestrian navigation systems using low-cost MEMS sensors face challenges in accurate step detection and walking direction estimation due to high bias variations and noise, especially in slow-walk scenarios, leading to erroneous step detection and orientation uncertainties, which are compounded by the device's uncoupled orientation with respect to the user's motion.
Innovation Solution
A system utilizing a 3-axis accelerometer with electronic circuits to generate and correlate acceleration signals, perform periodicity checks, and estimate walking steps, combined with attitude estimation to determine the device's orientation relative to the user's motion, enabling robust step counting and accurate direction sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-cost MEMS accelerometers are used for pedestrian navigation, then device cost is reduced, but measurement precision deteriorates due to high bias variations and noise
Solution Approach 1:
The patent introduces an intermediary processing system that includes a signal generator creating reference acceleration signals, a correlator comparing reference signals with actual sensor outputs, and a peak detector identifying step events. This intermediary system filters out noise and bias variations from low-cost MEMS accelerometers, enabling accurate step detection despite the poor quality of raw sensor data.
Solution Approach 2:
The patent creates a copy of the expected acceleration pattern by generating reference acceleration signals that mimic normal walking patterns. By correlating these reference signals with actual sensor data, the system can identify steps based on pattern matching rather than relying on absolute acceleration threshold detection, thereby overcoming the noise and bias issues inherent in low-cost sensors.
2Device complexity
If threshold-based step detection is used with low-cost accelerometers, then detection simplicity is improved, but reliability deteriorates due to erroneous step detection in slow-walk scenarios
Solution Approach 1:
Instead of directly thresholding raw accelerometer signals, the patent introduces a correlation-based intermediary process. The system generates reference acceleration patterns, correlates them with actual sensor data through a sliding window, and uses peak detection on the correlation output to identify steps. This intermediary correlation process effectively filters out false positives that would occur with simple thresholding, especially during slow walking when acceleration magnitudes are small.
Solution Approach 2:
The patent performs preliminary action by pre-generating reference acceleration signals that represent expected walking patterns before comparing them with actual sensor data. This preparation of reference patterns enables the system to anticipate and recognize valid step events while rejecting spurious signals, improving reliability without significantly increasing computational complexity during real-time operation.
3Adaptability or versatility
If device orientation is uncoupled from user motion orientation, then device versatility is improved, but measurement precision deteriorates due to orientation uncertainties
Solution Approach 1:
The patent implements a universal step detection algorithm that works regardless of device orientation or placement. By using correlation-based detection that identifies characteristic walking patterns in the acceleration data, the system can accurately detect steps whether the device is held in hand, placed in a pocket, worn on the body, or mounted in various orientations, thus achieving multi-functionality and adaptability.
Solution Approach 2:
The correlation process acts as an intermediary that transforms orientation-dependent raw acceleration signals into orientation-independent step detection results. By comparing the pattern of acceleration variations rather than absolute values, the system eliminates the influence of device orientation, allowing accurate step counting and direction estimation regardless of how the device is positioned relative to the user's motion.
Data Source
AI summary
A system for pedestrian use includes an accelerometer having multiple electronic sensors; an electronic circuit operable to generate a signal stream representing magnitude of overall acceleration sensed by the accelerometer, and to electronically correlate a sliding window of the signal stream with itself to produce peaks at least some of which represent walking steps, and further operable to electronically execute a periodicity check to compare different step periods for similarity, and if sufficiently similar then to update a portion of the circuit substantially representing a walking-step count; and an electronic display responsive to the electronic circuit to display information at least in part based on the step count. Other systems, electronic circuits and processes are disclosed.