Auxiliary Sensor Gesture Recognition Start Stop Detection
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Solution Overview
Problem
Conventional gestural systems have poor recognition rates for detecting gestures, particularly in identifying start and stop portions of movements, which hinders effective human-body-based input mechanisms for controlling electronic devices.
Innovation Solution
The use of multiple sensors, such as MEMS sensors and capacitive touch sensors, integrated into wearable devices to reconstruct gestures by aggregating data and employing power-saving features, allowing for accurate detection of start and stop points through fusion of sensor data and efficient power management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional gestural systems use simple detection methods, then device complexity is reduced, but gesture recognition accuracy deteriorates
Solution Approach 1:
The patent combines multiple sensors (accelerometer, gyroscope, capacitive touch sensor) into an integrated sensing system. The auxiliary capacitive touch sensor is merged with the motion sensors to detect both movement and contact events, enabling accurate identification of gesture start and stop portions without requiring complex separate detection systems.
Solution Approach 2:
The auxiliary sensor serves multiple functions: detecting gesture start/stop events, providing contact information, and enabling power management. This multi-functional approach improves recognition accuracy without proportionally increasing system complexity, as one sensor component performs several detection tasks.
2Measurement precision
If continuous sensor monitoring is used to improve gesture detection, then recognition accuracy is improved, but energy consumption increases
Solution Approach 1:
The system uses the auxiliary capacitive touch sensor to detect contact events that trigger periodic motion sensor sampling. Instead of continuous monitoring, the motion sensors are activated only when the auxiliary sensor detects a touch event, creating a periodic sampling pattern that maintains detection accuracy while significantly reducing overall energy consumption during idle periods.
Solution Approach 2:
The auxiliary sensor acts as a self-service trigger mechanism that automatically activates the power-consuming motion sensors only when needed. The system uses the low-power auxiliary sensor to monitor for gesture events, and only engages the higher-power sensors when the auxiliary sensor indicates a gesture is occurring, making the power consumption self-regulating based on actual usage needs.
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 enhances gesture recognition rates and energy efficiency by enabling precise detection of micro-gestures and complex interactions with electronic devices, while conserving battery power through intelligent power management and reduced reliance on camera-based systems.
Implementation Method 1
data for recognition of start and/or stop portions of the gesture using an auxiliary sensor, such as a capacitive touch sensor
Implementation Method 2
The use of multiple sensors, such as MEMS sensors and capacitive touch sensors
Data Source
AI summary
Described are apparatus and methods for reconstructing a gesture by aggregating various data from various sensors, including data for recognition of start and/or stop portions of the gesture using an auxiliary sensor, such as a capacitive touch sensor or a MEMS sensor. In a specific embodiment, power savings features are included to preserve the energy stored on the battery of a sensing device.