Power-assisted System Research Articles

A Novel Personalized Strategy for Hip Joint Flexion Assistance Based on Human Physiological State.

Soft exosuits have emerged as potent assistive tools for walking support and rehabilitation training. However, most existing soft exosuit systems rely on preset assistance modes, which may not accurately align with individual physiological states and movement requirements, leading to variable user experiences and efficacy. While existing human-in-the-loop (HIL) research predominantly focuses on optimizing metabolic cost and torque difference parameters, there is a notable absence of real-time monitoring methods that closely reflect the human body's physiological state and strategies that dynamically indicate walking efficiency. Motivated by this, we developed a novel personalized power-assist system. This system optimizes the power-assist output of the hip joint by monitoring the user's physiological and motion signals in real time, including heart rate (HR), blood oxygen saturation (SpO2), and inertial measurement unit (IMU) data, to assist hip flexion based on feedback. The findings from a metabolic expenditure trial demonstrate that the innovative soft exosuit, which is based on a Physiological State Monitoring Control (PSMC) system, achieves a reduction of 7.81% in metabolic expenditure during treadmill walking at a speed of 3.5 km/h compared to walking without the assistance of the exosuit. Additionally, during continuous exercise with varying intensities, the metabolic consumption level is reduced by 5.1%, 5.8%, and 8.2% at speeds of 2, 4, and 6 km per hour, respectively. These results support the design of a novel hip flexion-assisting soft exosuit, demonstrating that applying different assistance forces in consideration of different physiological states is a reasonable approach to reducing metabolic consumption.

Development of Mobility Type Upper Limb Power Assist System —Mechanism and Design of Power Assist Device—

In fruit cultivation, viticulture requires the longest working hours in extended arm postures, much of which is carried out in standing postures to accumulate fatigue on arms, shoulders, and legs: a tough working environment. In this study, we propose a power assist system to assist its users in their extended arm work while they move in vineyards. The proposed system largely consists of a mobile robot, a power assist device for work, and a control system. The mobile robot is structured with a tracked vehicle for rough terrain arranged on its left and right sides so that the users can sit between the two vehicles and be assisted by the power assist device for work installed on it. The power assist device for work with a single linear actuator utilizing a linkage mechanism has the function to retain users’ hand attitude angles while assisting the flexion and extension movements of their shoulder, elbow, and carpometacarpal joints. Then, we verify by simulations the effects that the arrangement and lengths of links will have on the carpometacarpal joints’ trajectories as well as on the hand attitude angles. Finally, in order to check the effectiveness of the proposed power assist device for work, we conducted the evaluation experiments for assumed grape-harvesting work and gibberellin treatments. As a result, we proved its work assisting effects from the muscle activity states as well as its applicability to other kinds of work by altering its linkage structure and hand support part.

Development of the Power Assist System for High Efficiency and Lightweight Wearable Robot in Unstructured Battlefield

The wearable robot system is designed to assist human skeletal and muscular systems for enhancing user’s abilities in various fields, including medical, industrial, and military. The military has an expanding need for wearable robots with the integration of surveillance/control systems and advanced equipment in unstructured battlefield environments. However, there is a lack of research on the design and mechanism of wearable robots, especially for power assist systems. This study proposes a lightweight wearable robot system that provides comfortable wear and muscle support effects in various movements for soldiers performing high-strength and endurance missions. The Power assist mechanism is described and verified, and the tasks that require power assist are analyzed. This study explain the system including its driving mechanism, control system, and mechanical design. Finally, the performance of the robot is verified through experiments and evaluations, demonstrating its effectiveness in muscle support.

The Validation of the Improvement Effect of Maneuverability on Power Assist System using Guidance Force of Toward the Planned Trajectory Considering Approachability

The Validation of the Improvement Effect of Maneuverability on Power Assist System using Guidance Force of Toward the Planned Trajectory Considering Approachability

Design of Permanent Magnet Synchronous Motor Power-assisted System Based on Field Oriented Control Algorithm

Aiming at the integrated surgical robot, a set of power-assisted control system is designed to overcome the transmission resistance between master and slave hands, so that the operator feels light and comfortable during operation. The system includes permanent magnet synchronous motor, driver, controller, torque sensor, upper computer. The field oriented control algorithm is discussed and is used to control the permanent magnet synchronous motor. STM32 is used as the main control chip, DRV8301 is used as the driving chip, and the upper computer software, which has human-computer interaction interface and real-time torque signal display interface, is written by C#. A non-contact torque sensor and corresponding signal processing module is designed. The experimental results show that with the operator’s start-stop and reversing action, the q-axis current of the motor changes rapidly, and the amplitude of steady-state changes is small. This means that the designed system has the advantages of stable assist torque and fast response.

Control Design of Observer-Based Virtual Soft Boundary for a Power-Assist System with Limited Operating Range

Control design of power-assist systems has been widely applied to human-robot interactive systems such as wearable exoskeleton systems, of which the range of motion limitation of human joints in the power-assist systems is essential. This paper presents a virtual soft boundary design for a human-robot cooperation system with a limited operating range. The proposed virtual soft boundary is realized by impedance control and integrated into the power-assist robot arm system; meanwhile, power-assist robot arm systems are typical human-in-the-loop systems, and the control of the power-assist system in performing in accordance with a human’s perception is a significant issue. Therefore, a model-based disturbance observer with a pseudo-derivative feedback feedforward (PDFF) compensator is designed to effectively estimate the human’s torque for an appropriate motor torque command. Experimental results show that the proposed control method can estimate the human torque exerted on the robot arm system to achieve a power-assist system, and the virtual soft boundary can be realized by the impedance control and integrated into the power-assist robot arm system.

Adipose Grafting for Volume and Scar Release.

Adipose fat grafting (AFG) is a popular technique used to add volume in the face, breasts, and other tissue deficient areas of the body. In terms of scar release, not only has fat provided additional soft tissue coverage but also the relief of pain in scars in those patients suffering from disease processes, such as complex regional pain syndrome with steroid-induced atrophy, burn scars, morphea, and lupus. The purpose of this article is to demonstrate the senior author's technique and outcomes of using AFG in the face and body for treating volume deficiency, atrophic scarring, and deformities.A retrospective chart review of 127 AFG procedures of the face and body from September 2006 to September 2019 was performed. Of these, 14 patients had scar releases performed with fat grafting of areas of scar contracture. Fat was harvested from the abdomen, thighs, and flanks using Toomey syringes or an enclosed power-assisted system with 3.7- or 3.0-mm cannulas. Grafting in small areas, such as the face, was performed with the 0.9-mm blunt cannula.The majority of AFG was completed in the face (45%), followed by breasts (22%), and scar contracture (16%). The mean volume of fat grafted in procedures involving the breasts, buttocks, and face was 102, 182, and 21 mL, respectively. For scar contracture, the mean volume was 38 mL and for deformations, 27 mL. Sixteen percent of the cohort required at least 1 additional AFG procedure to achieve satisfactory results. There were no major complications, such as skin loss, vascular injury, embolization, or blindness. Minor complications, such as erythema, edema, and hematoma at the fat harvest or graft site, did occur and were managed with local measures.Autologous fat grafting has consistently resulted in volume correction. In addition, in patients with autoimmune disorders, burn scars, and retracted scars, not only has there been volume correction but also decreased pain in the area of treatment. In our series of patients, we described our technique of AFG for the face, body, and scar contracture. Our results demonstrate that AFG remains an inexpensive, safe, and effective treatment option to achieve volume.

A Power Assistant Algorithm Based on Human–Robot Interaction Analysis for Improving System Efficiency and Riding Experience of E-Bikes

As robots are becoming more accessible in our daily lives, the interest in physical human–robot interaction (HRI) is rapidly increasing. An electric bicycle (E-bike) is one of the best examples of HRI, because a rider simultaneously actuates the rear wheel of the E-bike in close proximity. Most commercially available E-bikes employ a control methodology known as a power assistant system (PAS). However, this type of system cannot offer fully efficient power assistance for E-bikes since it does not account for the biomechanics of riders. In order to address this issue, we propose a control algorithm to increase the efficiency and enhance the riding experience of E-bikes by implementing the control parameters acquired from analyses of human leg kinematics and muscular dynamics. To validate the proposed algorithm, we have evaluated and compared the performance of E-bikes in three different conditions: (1) without power assistance, (2) assistance with a PAS algorithm, and (3) assistance with the proposed algorithm. Our algorithm required 5.09% less human energy consumption than the PAS algorithm and 11.01% less energy consumption than a bicycle operated without power assistance. Our algorithm also increased velocity stability by 11.89% and acceleration stability by 27.28%, and decreased jerk by 12.36% in comparison to the PAS algorithm.

Development of 1-DOF Mechanomyography-Based Elbow Power Assist System

Development of 1-DOF Mechanomyography-Based Elbow Power Assist System

Study on Operability Improvement of Power Assist System

Study on Operability Improvement of Power Assist System

Analysis of Velocity Pattern of a Power-Assisted Mobile Robot

This paper aims to analyze the velocity pattern of a power-assisted mobile robot when the operator performs operation without any discomfort. Power-assist systems for mobile robots such as wheelchairs and conveyance carriers are extremely effective in alleviating the physical burden on operators when they carry heavy objects. Although the velocity control based power-assist system has an advantage that it can be easily realized, the problem lies in that the system becomes unstable when the operator has high stiffness. Variable impedance control based on impedance estimation of the operator is effective at solving this problem. To realize operator impedance estimation, it is necessary to know the intended robot’s motion of a person. In this study, as a preliminary step to estimate the operator’s impedance, the velocity pattern when the operator performs natural operation of the robot through the power-assist system is analyzed. The results confirm that the natural velocity pattern can be approximated by a velocity pattern connecting two minimum jerk trajectories.

Development of a Wireless Surface Electromyography (sEMG) Signal Acquisition Device for Power-Assisted Wheelchair System

Muscle fatigue due to long-term of manual wheelchair propulsion is an issue faced by most of users. A power-assisted wheelchair developed to amplify propulsion force that activated by surface electromyography (sEMG). A sEMG detection wireless device to trigger the assistive system is an advantage to ease installation on user’s body and wheelchair which is developed in this study. A device that operated on Arduino Nano processor connected to 2 (two) Myoware sEMG sensors to record muscles electrical potential (EP), recognise the pattern and activate DC motors wirelessly connected through radio frequency. Data monitoring on personal computer and smart phone associated with Bluetooth to store and ease observation on recorded information. Tested on 1 healthy participant by propelling a manual wheelchair on tiled floor. Developed device’s performance tested and the result are average sampling rate (33.55 ms) and average reading latency was just 12.38 ms. Compared to wired device, sampling rate is faster by % and reading latency slower by 1.04 %. Result demonstrate that developed wireless device would improve in speed in signal reading and enhancement on reading latency is needed to provide a reliable device for power-assisted system in the future.

Proposal of a Power Assist System When Walking Inverted Pendulum Type Personal Mobility Vehicle

Proposal of a Power Assist System When Walking Inverted Pendulum Type Personal Mobility Vehicle

Study on Arm Type Power Assist System

Study on Arm Type Power Assist System

Design and Control of a Power-Assist System for Pedal Operation

Design and Control of a Power-Assist System for Pedal Operation

Feature Extraction of Shoulder Joint's Voluntary Flexion-Extension Movement Based on Electroencephalography Signals for Power Assistance.

Brain-Machine Interface (BMI) has been considered as an effective way to help and support both the disabled rehabilitation and healthy individuals’ daily lives to use their brain activity information instead of their bodies. In order to reduce costs and control exoskeleton robots better, we aim to estimate the necessary torque information for a subject from his/her electroencephalography (EEG) signals when using an exoskeleton robot to perform the power assistance of the upper limb without using external torque sensors nor electromyography (EMG) sensors. In this paper, we focus on extracting the motion-relevant EEG signals’ features of the shoulder joint, which is the most complex joint in the human’s body, to construct a power assistance system using wearable upper limb exoskeleton robots with BMI technology. We extract the characteristic EEG signals when the shoulder joint is doing flexion and extension movement freely which are the main motions of the shoulder joint needed to be assisted. Independent component analysis (ICA) is used to extract the source information of neural components, and then the average method is used to extract the characteristic signals that are fundamental to achieve the control. The proposed approach has been experimentally verified. The results show that EEG signals begin to increase at 300–400 ms before the motion and then decrease at the beginning of the generation of EMG signals, and the peaks appear at about one second after the motion. At the same time, we also confirmed the relationship between the change of EMG signals and the EEG signals on the time dimension, and these results also provide a theoretical basis for the delay parameter in the linear model which will be used to estimate the necessary torque information in future. Our results suggest that the estimation of torque information based on EEG signals is feasible, and demonstrate the potential of using EEG signals via the control of brain-machine interface to support human activities continuously.

Cognition-based variable admittance control for active compliance in flexible manipulation of heavy objects with a power-assist robotic system

In the first step, a 1-DOF power-assist robotic system (PARS) is developed for lifting lightweight objects. Dynamics for human–robot co-manipulation of objects is derived that considers human cognition (weight perception). Then, admittance control with position feedback and velocity controller is derived using weight perception-based dynamics. Human subjects lift an object with the PARS, and HRI (human–robot interaction) and system characteristics are analyzed. A comprehensive scheme is developed to evaluate the HRI and performance. HRI is expressed in terms of physical HRI (maneuverability, motion, safety, stability, naturalness) and cognitive HRI (workload, trust), and performance is expressed in terms of manipulation efficiency and precision. To follow the guidance of ISO/TS 15066, hazard analysis and risk assessment are conducted. A constrained optimization algorithm is proposed to determine the values of the control parameters that produce optimum HRI and performance with lowest risk. Results show that consideration of weight perception in dynamics and control helps achieve optimum HRI and performance for a set of hard constraints. In the second step, a weight perception-based novel variable admittance control scheme is proposed as an active compliance to the system, which enhances the physical HRI, trust, precision and efficiency by 53.05%, 46.78%, 3.84% and 4.98%, respectively, and reduces workload by 35.38% and thus helps achieve optimum HRI and performance for a set of soft constraints. The risk reduces due to the active compliance. Then, effectiveness of the optimization and control algorithms is validated using a multi-DOF PARS for manipulating heavy objects, and intuitive and natural HRI and performance for power-assisted heavy object manipulation are achieved through calibrating HRI and performance with that for manipulation of lightweight object.

脳波分析に基づいたBrain-Machine Interfaceパワーアシストシステムの構築

脳波分析に基づいたBrain-Machine Interfaceパワーアシストシステムの構築

Development of Power Assistance System for Transfer Assist Equipment

Development of Power Assistance System for Transfer Assist Equipment

Control of Power Assist System for Easy Positioning

Control of Power Assist System for Easy Positioning