Maximum Likelihood Estimation based Explicit Intention Recognition System
Process
Experiment Set Up
Experiment Environment
6 Kind of Explicit Intention(Finger or Wrist Motion) Defined
Focused on Availability and Necessity
30 Repetition for Each Explicit Intention
Maintained for About 0.2 Second
Performance Evaluation
Recognition Method
Training Set: Randomly Selected 15 Trials for Each Intention
Test Set: 15 Trials Which is Not Selected as Training Set
Cross-validation is Used
Gaussian Model based Maximum Likelihood Estimation is Used
Result
Shows 96.67% of Average Recognition Accuracy
Motion Duration Recogition Based Extrinsic Intention Recognition System
Process
Experiment Set Up
Experiment Environment
Motion Start: Holding Grab Motion
Motion End: Changing Grab to Extension
Recognize Time between Motion Start Point and Motion End Point
2 Different Motion is Used
Short Motion: Duration Under 0.5 Second
Long Motion: Duration Over 1 Second
Performance Evaluation
Do Not Need Training
Selected Answer Section by using Accelerometer Data from Finger
Identified the Time Error by Comparing Answer Section and Recognized Section (△e_1& △e_2 in the figure below)
Motion Duration Time Recognition Method
Result
Short Motion: Occurs Average 0.08 Second of Duration Time Error
Long Motion: Occurs Average 0.14 Second of Duration Time Error
IoT Interaction
IoT Device Control System
Transmit the Acquired Data from Wearable Device to Computer
User Intention Recognition on Computer
Control PC Software
Google Map
Media Player
Control IoT Device
Smart Bulb
Smart Door Lock
Smart Switch
Smart Temperature Control System
Smart Device Control System based on Wrist Type Wearable Device
Explicit Intention Recognition by Using Wrist-type Wearable Device
Introduction
The project aims to develop a wrist-type wearable sensor system for IoT interaction.
To achieve the goal of the project, we develop wrist-type wearable sensor prototype which records multi-channel EMG and 3 axis accelerometer and gyroscope.
Data from the wrist-type wearable device is transmitted to computer by bluetooth communication module.
The various signal processing and data analysis including explicit intention recognition is progressed on computer.
Control command correspond to the recognized explicit intention is sent to various smart devices.
IoT interaction by using the control command is the final goal of the project.