Pedometer Step Counting with Dynamic Amplitude Threshold
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Solution Overview
Problem
Conventional pedometers face inaccuracies in step counting due to swinging movements and false steps, particularly in low-power devices, which require computationally expensive calculations to improve accuracy, impacting battery life.
Innovation Solution
A method that involves deriving amplitudes from raw sensor data, comparing them to an amplitude threshold, dynamically adjusting the threshold based on gait type, and applying a post-filter to reduce false readings, all performed within a low-computation MicroController Unit (MCU) to filter out swinging movements and false steps, thereby simplifying calculations and conserving power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sophisticated software with increased mathematical calculations is used to improve step count accuracy, then measurement precision is improved, but use of energy worsens due to computational expense impacting battery life
Solution Approach 1:
The patent segments the step detection process into distinct stages: raw accelerometer data acquisition, amplitude derivation, threshold comparison, and post-filtering. Each stage processes only essential information, avoiding computationally expensive operations while maintaining accuracy. The segmentation allows the system to achieve precise step counting without requiring sophisticated mathematical calculations that would consume excessive energy.
Solution Approach 2:
The patent extracts only the essential feature (amplitude of acceleration) from the raw sensor data for step detection, discarding unnecessary information. By focusing solely on amplitude threshold comparison rather than performing complex mathematical analysis on the entire accelerometer signal, the system achieves accurate step counting with minimal computational expense, thereby preserving battery life.
2Use of energy by moving object
If simple amplitude threshold comparison is used to reduce computational expense, then use of energy is improved, but measurement precision worsens due to false steps from swinging movements
Solution Approach 1:
The patent implements feedback through the post-filter stage that uses the time intervals between detected steps to validate step detections. When steps are detected too rapidly (indicating swinging movements rather than actual steps), the post-filter corrects false positives by adjusting the step count based on physiologically plausible step rates. This feedback mechanism maintains measurement precision without requiring additional computational resources during the primary detection phase.
Solution Approach 2:
The patent performs preliminary amplitude threshold comparison to identify potential steps, then applies post-filtering to eliminate false detections. This two-stage approach allows the system to use simple, low-power threshold comparison for initial detection while correcting errors afterward, achieving both low power consumption and high measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively filters out false steps and swinging movements while maintaining low power consumption, enhancing the accuracy of step counting without significantly impacting battery life, even in low-power devices.
Implementation Method 1
Conventional pedometers use accelerometers to sense body motion
Implementation Method 2
Today's pedometers may utilize MEMS inertial sensors and sophisticated software to detect steps
Data Source
AI summary
Methods and systems for determining a user's steps in portable device include deriving amplitudes from raw sensor data; comparing the amplitudes to an amplitude threshold, and counting a step when one of the amplitudes exceeds the amplitude threshold to obtain a step count; determining a current gait type based on the step count; dynamically adjusting the amplitude threshold in order to reduce effects of swinging movements and false steps; and applying a post filter to the step count based on time between steps and a minimum number of prior consecutive steps to derive a filtered step count that reduces false readings due to short bursts of rapid movement by the user.