Active Orthotic Force Control Using Bioelectric Intention Sensing
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Solution Overview
Problem
Current active orthotic devices struggle to mimic the natural movement of healthy individuals, particularly when interacting with external objects, as they fail to accurately control the movement of limbs in a way that corresponds to the wearer's intentions.
Innovation Solution
The method involves obtaining bioelectric signals from sensors to predict the intended application force and combining them with force signals from sensing devices to generate control signals for the actuators, allowing the orthotic device to intuitively and automatically adjust its movements based on the wearer's intentions, thereby improving the correspondence between the wearer's intentions and the device's actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active orthotic devices use actuators to impart movement to limbs, then motor activity can be restored or improved, but the devices fail to properly mimic natural movement and correspond to the wearer's intention
Solution Approach 1:
The patent implements a feedback control system where force sensors mounted around the upper limb measure radially directed muscle pressure, and this force signal is fed back to the controller. The controller uses this feedback to adjust the exoskeleton's movement in real-time, ensuring that the device's actions correspond to the wearer's actual intention rather than relying on pre-programmed or open-loop control.
Solution Approach 2:
The patent replaces traditional mechanical control systems with a sensor-based detection and control system. Instead of using complex mechanical linkages or pre-set mechanical mechanisms to control movement, the system uses force sensors to detect muscle pressure and a controller with machine learning algorithms to translate this into appropriate actuator commands, enabling more natural and adaptive movement.
2Measurement precision
If force sensors are used to measure muscle pressure, then wearer intention can be detected more accurately, but device complexity increases
Solution Approach 1:
The patent introduces force sensors as intermediary devices that indirectly measure wearer intention through radially directed muscle pressure rather than directly measuring neural signals or requiring complex imaging. This intermediary measurement approach simplifies the detection system while maintaining accuracy, as the force sensors provide a direct physical measurement of the wearer's intent to move.
Solution Approach 2:
The patent changes the measurement parameter from direct neural or positional monitoring to force-based muscle pressure measurement. By measuring the radial force exerted by muscles during contraction, the system obtains a direct indicator of movement intention that is easier to detect and process than traditional EMG or imaging methods, thereby improving measurement precision without proportionally increasing complexity.
3Adaptability or versatility
If machine learning algorithms process force signals, then motion and force intention can be detected, but processing complexity and computational requirements increase
Solution Approach 1:
The patent applies machine learning algorithms selectively to process the force signals from sensors, rather than attempting to analyze all possible physiological signals. The algorithm focuses on detecting the specific patterns in radially directed muscle pressure that indicate movement intention, applying computational power only where needed to translate force signals into control commands, thus balancing adaptability with manageable complexity.
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 enables the active orthotic device to effectively control limb movements, allowing for natural and well-controlled interactions with objects, such as gripping and releasing, by determining the intended application force and adjusting the actuators accordingly.
Implementation Method 1
Such bioelectric sensors include so-called electromyography (EMG) sensors, which may be implanted (intramuscular electromyography, iEMG) or applied to the skin of the individual (surface electromyography, sEMG). An EMG sensor detects the electric potential generated by muscle cells when these cells are electrically or neurologically activated.
Implementation Method 2
obtaining a force signal from a force sensing device associated with the respective set of actuators and/or the respective limb
Data Source
AI summary
An active orthotic device, e.g. a hand orthosis, is attached to one or more limbs of a human subject and comprises a respective set of actuators (21) for moving a respective limb (1A) among the one or more limbs. A method for controlling the orthotic device comprises obtaining one or more bioelectric signals, [S(t)], from one or more bioelectric sensors (10) attached to or implanted in the human subject; processing the one or more bioelectric signals, [5(t)j, for prediction of an intended application force, FA(t), of the respective limb (1A) onto an object; obtaining a force signal, PA(t), from a force sensing device (22) associated with the respective set of actuators (21) and/or the respective limb (1A); and generating, as a function of a momentary difference, e(t), between the intended application force, FA(t), and the force signal, PA(t), a respective set of control signals, it(t), for the respective set of actuators (21).