Upper Limb Motion Support With Bio-Signal Guided Cooperative Arm Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current upper limb motion support systems for hemiplegic individuals are inadequate as they lack durability and portability, and existing robot arms fail to accurately estimate user intention, leading to inefficient and inaccurate work performance, particularly in desktop tasks like cooking and object assembly.
Innovation Solution
An upper limb motion support apparatus with an articulated arm, environment imaging, biological signal detection, and a controller that recognizes and mimics the user's motion intentions by capturing environmental images, detecting biological signals, and adjusting the articulated arm and end effector to perform cooperative motions in conjunction with the user's unaffected hand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Weight of moving object
If a robot arm is made compact and lightweight for portability, then it can be mounted on a table and used by hemiplegic persons, but its durability and structural stability deteriorate
Solution Approach 1:
The patent combines multiple functions into an integrated system: the robot arm (artculated arm) is merged with the support structure, and the control system integrates biological signal detection, image recognition, and motion coordination. This merging allows the system to achieve reliable performance through functional integration rather than relying solely on individual component robustness.
Solution Approach 2:
The robot arm system is designed to perform multiple functions: it can assist with various desktop tasks (cooking, object assembly, writing), detect multiple types of biological signals (EMG, EEG), capture environmental images, and coordinate motions autonomously. This multi-functionality compensates for the lightweight design by creating a versatile assistive system that provides reliable support across diverse applications.
2Productivity
If the robot arm autonomously estimates user intention, then work efficiency improves, but the complexity of the control system increases
Solution Approach 1:
The system implements multiple feedback loops: biological signal detection provides real-time feedback on user intention, image recognition provides feedback on environmental context, and the coordination control provides feedback on motion execution. This multi-layered feedback enables autonomous intention estimation while managing complexity through structured information flow from detection to control.
Solution Approach 2:
The patent replaces traditional mechanical control interfaces (buttons, switches, physical levers) with biological signal detection (EMG, EEG sensors) and vision-based recognition. This substitution eliminates complex mechanical control mechanisms while enabling intuitive, autonomous intention estimation through physiological and visual data processing.
3Ease of operation
If the robot arm performs cooperative motion with the unaffected hand, then workload balance improves, but the difficulty of detecting and measuring user intention increases
Solution Approach 1:
The system employs multiple detection modalities (EMG sensors for muscle signals, EEG sensors for brain waves, image cameras for visual context) to universally capture user intention across different physiological states and task types. This multi-functional detection approach makes the system robust in detecting intention despite the complexity of interpreting diverse biological signals during cooperative motion.
Solution Approach 2:
The system introduces intermediate processing layers between biological signals and control commands: image recognition acts as an intermediary to interpret visual context, and the coordination control algorithm serves as a mediator to translate combined biological and visual data into coordinated motion commands. These intermediaries simplify the direct mapping problem while maintaining accurate intention detection.
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
Significantly enhances work efficiency and reduces workload by accurately recognizing user intentions and performing coordinated motions, improving the quality of life for hemiplegic individuals and enabling more effective cooperative work with both hands.
Implementation Method 1
a biological signal detection unit that detects electric potential as a biological signal generated in association with the upper limb motion of the operator
Data Source
Figure 1
Figure 2
Figure 3
AI summary
An upper limb motion support apparatus and an upper limb motion support system which are capable of significantly improving the enhancement of an operator's work efficiency and the reduction of their workload are proposed. A controller which causes an articulated arm and an end effector to perform three-dimensional motion according to the operator's intention based on a biological signal acquired by a biological signal detection unit causes the articulated arm and the end effector to perform cooperative motion in conjunction with the operator's upper limb motion by referring to content recognized by an upper limb motion recognition unit.