Mobile BAC Detection via Passive Gait Analysis

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Solution Overview

Problem

Existing devices for detecting blood alcohol content (BAC) require active user engagement, are often standalone, and lack the use of reliable gait information, leading to reduced accuracy and adoption.

Innovation Solution

A mobile sensing device equipped with accelerometers and gyroscopes that passively detects BAC and impairment levels using machine learning to classify gait attributes, allowing for passive operation and integration with daily devices like smartphones.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If active user engagement is required (e.g., blowing into breathalyzer or taking challenges), then detection accuracy can be improved, but ease of operation deteriorates and adoption is reduced

Engineering Contradiction:

ImproveBAC detection accuracyVSAvoiduser engagement requirement

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs self-service by automatically collecting gait data from the mobile device's sensors without requiring active user participation. The machine learning model processes the sensor data autonomously to determine BAC levels, eliminating the need for users to blow into breathalyzers or complete challenges.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces mechanical/active detection methods (breathalyzer blowing, physical challenges) with passive sensor-based detection. The mobile device's accelerometer and gyroscope capture gait information automatically, substituting active mechanical interaction with passive electronic sensing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If dedicated stand-alone devices are used (e.g., SCRAM device, Kisai watch), then detection function is specialized, but device complexity increases and scalability is reduced

Engineering Contradiction:

Improvedetection function specializationVSAvoidstand-alone device requirement

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies universality by using a common mobile device that users already possess for multiple purposes. The same device that serves for communication and daily tasks is also used for BAC detection, eliminating the need for separate dedicated devices and reducing overall system complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent merges the BAC detection functionality with the existing mobile device ecosystem. By combining gait analysis capabilities with the mobile device's existing sensors and processing power, the system eliminates the need for separate hardware devices while maintaining detection reliability.

Inventive Principle:

Principle #5Merging (Combining)

3Device complexity

If only heart rate and temperature data are used, then device complexity is reduced, but measurement precision deteriorates due to lack of gait information

Engineering Contradiction:

Improvesensor requirementsVSAvoidBAC detection accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent segments the detection process into multiple independent data sources: gait data from accelerometer and gyroscope, heart rate data, and temperature data. Each sensor type contributes specific information, with gait analysis providing the primary indicator of intoxication while physiological data serves as supporting evidence.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent uses a composite approach by combining multiple types of sensor data (gait, heart rate, temperature) to create a comprehensive BAC assessment. This multi-modal data fusion improves measurement precision by leveraging the strengths of different sensing modalities rather than relying on a single sensor type.

Inventive Principle:

Principle #40Composite materials

4Ease of operation

If passive detection without gait analysis is used, then ease of operation is improved, but measurement precision deteriorates due to insufficient data features

Engineering Contradiction:

Improvepassive operationVSAvoidBAC detection accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent adds another dimension to passive detection by incorporating spatial and temporal analysis of gait data through accelerometer and gyroscope measurements. This transforms simple motion detection into sophisticated gait analysis, extracting multiple features (cadence, symmetry, variability) that provide rich information about intoxication levels while maintaining passive operation.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS10539549B2Mobile blood alcohol content and impairment sensing device

Publication Date: 2020.01.21 WORCESTER POLYTECHNIC INSTITUTE

AI summary

In a mobile sensing device, a method of detecting blood alcohol content includes receiving time-series gait data from at least one sensor of the mobile sensing device as a user walks and detecting a set of attributes associated with the time-series gait data, each attribute of the set of attributes related to the user's gait. The method includes comparing the set of attributes with a machine learning classification model learned from a training data set of attributes to determine at least one of a blood alcohol content range of the user and an impairment level of the user and outputting a notification associated with the at least one of the blood alcohol content range of the user and the impairment level of the user.