Sensorless model-based tension control for a cable-driven exosuit

TL;DR

This work demonstrates sensorless tension control for a cable-driven upper-limb exosuit by integrating a data-driven friction identification with a model-based tension controller to regulate cable tension without a load cell. A Bowden-transmission model captures friction losses, and two linear relations between motor torque and output tension are identified for raising and lowering, enabling real-time tension regulation with gravity compensation. In healthy participants, the approach reduces activity in shoulder muscles during arm elevation and preserves kinematic tracking, though movement smoothness and user comfort require further improvement due to ergonomic constraints. The findings show feasibility and potential for simpler, more affordable exosuits, while outlining practical considerations for friction modelling, control tuning, and cuff design to enhance user comfort and long-term usability.

Abstract

Cable-driven exosuits have the potential to support individuals with motor disabilities across the continuum of care. When supporting a limb with a cable, force sensors are often used to measure tension. However, force sensors add cost, complexity, and distal components. This paper presents a design and control approach to remove the force sensor from an upper limb cable-driven exosuit. A mechanical design for the exosuit was developed to maximize passive transparency. Then, a data-driven friction identification was conducted on a mannequin test bench to design a model-based tension controller. Seventeen healthy participants raised and lowered their right arms to evaluate tension tracking, movement quality, and muscular effort. Questionnaires on discomfort, physical exertion, and fatigue were collected. The proposed strategy allowed tracking the desired assistive torque with an RMSE of 0.71 Nm (18%) at 50% gravity support. During the raising phase, the EMG signals of the anterior deltoid, trapezius, and pectoralis major were reduced on average compared to the no-suit condition by 30%, 38%, and 38%, respectively. The posterior deltoid activity was increased by 32% during lowering. Position tracking was not significantly altered, whereas movement smoothness significantly decreased. This work demonstrates the feasibility and effectiveness of removing the force sensor from a cable-driven exosuit. A significant increase in discomfort in the lower neck and right shoulder indicated that the ergonomics of the suit could be improved. Overall this work paves the way towards simpler and more affordable exosuits.

Figures (10)

• Figure 1: (\ref{['fig:tdu_A']}) Picture of the TDU in the final assembled configuration with major electromechanical components labeled. (\ref{['fig:tdu_B']}) Functioning principle of the exosuit. Cable tension, generated in the TDU by the motor, is transmitted along the body through the Bowden sheath system. This results in an assistive torque about the glenohumeral joint of the wearer, supporting the arm against gravity. (\ref{['fig:tdu_C']}) Rendering of the swivelling shoulder cuff in Solidworks 2021. (\ref{['fig:tdu_D']}) Setup for the model identification experiments. The mannequin, modified with a motorized arm, wears the exosuit.
• Figure 2: Control block diagram. The "gravity assistance model" block maps the current humeral angle of elevation to the desired output tension based on the anthropometrics of the user and desired support level. The desired tension is sent to the "transmission inverse model and friction compensation block" which computes the desired motor torque as a function of the humeral elevation speed. The desired torque is sent to the motor which runs a low-level torque controller. Finally, the motor output torque acts on the cable through the pulley and is transmitted to the arm through the Bowden sheath mechanism.
• Figure 3: Study protocol. Participants were first explained the full protocol and had the opportunity to perform a training task without the suit for familiarization. The task was repeated for four conditions: no-suit (no), pretension of 10 N (pre), 25% gravity support (25%), 50% gravity support (50%). The no-suit condition was always performed as the first to measure the baseline EMG values of each participant. The other three conditions were randomized in order to exclude effects from habituation to the device. A 5-minute break was given to each participant between conditions while a set of questionnaires were administered. For each support condition, three movement speed conditions were tested. The slow condition had a peak speed of 60$\frac{^\circ}{s}$ (V1), the medium condition 120$\frac{^\circ}{s}$ (V2), and the fast condition 180$\frac{^\circ}{s}$ (V3). At the end of the study the exosuit and EMG system was removed, and the participant thanked with a cookie.
• Figure 4: Linear regressions of the desired cable tension ($T_{out,des}$) and the TDU motor torque ($\tau_{des}$) required. The graph axes are presented this way to reflect the controller architecture (Fig. \ref{['fig:controller']}). The data and regression line for the raising phase is shown in blue, while the lowering phase is shown in orange. Slope and intercept are displayed along with goodness of fit ($R^2$).
• Figure 5: Results for one participant averaged over the nine repetitions. The solid lines represent the average value, the shaded area is the standard deviation. The four support conditions, "No", "Pre", "25%", and "50%", are represented with the colors purple, blue, red, and yellow, respectively. Each column shows a velocity condition (V1, V2, V3). A) Humeral angle of elevation ($\theta_{AOE}$). B and C) Supporting torque acting at the shoulder joint and the cable tension acting on the anchor point, respectively, where the black line indicates the reference signal. D and E) EMG envelope of the anterior deltoid and the posterior deltoid, respectively.