Human-activity-centered measurement system:challenges from laboratory to the real environment in assistive gait wearable robotics

Assistive gait wearable robots (AGWR) have shown a great advancement in developing intelligent devices to assist human in their activities of daily living (ADLs). The rapid technological advancement in sensory technology, actuators, materials and computational intelligence has sped up this development process towards more practical and smart AGWR. However, most assistive gait wearable robots are still confined to be controlled, assessed indoor and within laboratory environments, limiting any potential to provide a real assistance and rehabilitation required to humans in the real environments. The gait assessment parameters play an important role not only in evaluating the patient progress and assistive device performance but also in controlling smart self-adaptable AGWR in real-time. The self-adaptable wearable robots must interactively conform to the changing environments and between users to provide optimal functionality and comfort. This paper discusses the performance parameters, such as comfortability, safety, adaptability, and energy consumption, which are required for the development of an intelligent AGWR for outdoor environments. The challenges to measuring the parameters using current systems for data collection and analysis using vision capture and wearable sensors are presented and discussed

Empowering and assisting natural human mobility: The simbiosis walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staf

Investigation of reducing fatigue and musculoskeletal disorder with passive actuators

Robotic systems such as exoskeletons can be effectively used in the reduction of fatigue and musculoskeletal disorders (MSD) associated with physical tasks, but robots which work in physical contact with humans pose problems with user safety. A novel approach to developing intrinsically safe robots is to use passive actuators which have the advantage of being safer, ensuring stability, high force/weight ratios and lower power consumption. It is however not clear how effective an exoskeleton utilizing passive actuators would be in reducing fatigue and the risk of MSD. This paper analyzes the benefit of using such a system with results from dynamic simulations and an experiment using a specially designed mechanism used for evaluation. Results indicate that fatigue and effort could be reduced if robot impedance is minimized. Experiments also highlighted issues of implementing such a system into practice. ©2010 IEEE

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

Human Activity Recognition and Control of Wearable Robots

abstract: Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity. This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU. This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.Dissertation/ThesisDoctoral Dissertation Aerospace Engineering 201

HPER Biomechanics Laboratory 2004 Annual Report: A Surveillance of the Neuromuscular System, Issue 3

This issue features 2004 - A Great Year for External Funding: Three Grants Awarded to Dr. Stergiou, Robotic Surgery Research is Funded by the Nebraska Research Initiative, Federal Grant is Awarded for the Study of the Development of Posture in Children with Cerebral Palsy, The Nebraska Research Initiative funds our Innovative Research in Gait Analysis, Collaboration with the Department of Surgery of the University of Nebraska Medical Center on the Effects of Peripheral Arterial Disease on Gait, Omaha Media Features Nicholas Stergiou, Dr. Stergiou participates in an NIH Review Panel, Prestigious Teaching Award for Dr. Stergiou, NASA Visits HPER Biomechanics Lab, Walking, a Neural Network and a Simple Robot, Sabbatical Strengthens Collaborations with Other Laboratories, Our Lab helps High School Students and Teachers, New Textbook Published and Other Exciting News/Continuing Collaboration.https://digitalcommons.unomaha.edu/nbcfnewsletter/1002/thumbnail.jp

Smart portable rehabilitation devices

BACKGROUND: The majority of current portable orthotic devices and rehabilitative braces provide stability, apply precise pressure, or help maintain alignment of the joints with out the capability for real time monitoring of the patient's motions and forces and without the ability for real time adjustments of the applied forces and motions. Improved technology has allowed for advancements where these devices can be designed to apply a form of tension to resist motion of the joint. These devices induce quicker recovery and are more effective at restoring proper biomechanics and improving muscle function. However, their shortcoming is in their inability to be adjusted in real-time, which is the most ideal form of a device for rehabilitation. This introduces a second class of devices beyond passive orthotics. It is comprised of "active" or powered devices, and although more complicated in design, they are definitely the most versatile. An active or powered orthotic, usually employs some type of actuator(s). METHODS: In this paper we present several new advancements in the area of smart rehabilitation devices that have been developed by the Northeastern University Robotics and Mechatronics Laboratory. They are all compact, wearable and portable devices and boast re-programmable, real time computer controlled functions as the central theme behind their operation. The sensory information and computer control of the three described devices make for highly efficient and versatile systems that represent a whole new breed in wearable rehabilitation devices. Their applications range from active-assistive rehabilitation to resistance exercise and even have applications in gait training. The three devices described are: a transportable continuous passive motion elbow device, a wearable electro-rheological fluid based knee resistance device, and a wearable electrical stimulation and biofeedback knee device. RESULTS: Laboratory tests of the devices demonstrated that they were able to meet their design objectives. The prototypes of portable rehabilitation devices presented here did demonstrate that these concepts are capable of the performance their commercially available but non-portable counterparts exhibit. CONCLUSION: Smart, portable devices with the ability for real time monitoring and adjustment open a new era in rehabilitation where the recovery process could be dramatically improved

Sensory augmentation:Integration of an auditory compass signal into human perception of space

Bio-mimetic approaches to restoring sensory function show great promise in that they rapidly produce perceptual experience, but have the disadvantage of being invasive. In contrast, sensory substitution approaches are non-invasive, but may lead to cognitive rather than perceptual experience. Here we introduce a new non-invasive approach that leads to fast and truly perceptual experience like bio-mimetic techniques. Instead of building on existing circuits at the neural level as done in bio-mimetics, we piggy-back on sensorimotor contingencies at the stimulus level. We convey head orientation to geomagnetic North, a reliable spatial relation not normally sensed by humans, by mimicking sensorimotor contingencies of distal sounds via head-related transfer functions. We demonstrate rapid and long-lasting integration into the perception of self-rotation. Short training with amplified or reduced rotation gain in the magnetic signal can expand or compress the perceived extent of vestibular self-rotation, even with the magnetic signal absent in the test. We argue that it is the reliability of the magnetic signal that allows vestibular spatial recalibration, and the coding scheme mimicking sensorimotor contingencies of distal sounds that permits fast integration. Hence we propose that contingency-mimetic feedback has great potential for creating sensory augmentation devices that achieve fast and genuinely perceptual experiences

Gait Dynamic Stability Analysis with Wearable Assistive Robots

abstract: Lower-limb wearable assistive robots could alter the users gait kinematics by inputting external power, which can be interpreted as mechanical perturbation to subject normal gait. The change in kinematics may affect the dynamic stability. This work attempts to understand the effects of different physical assistance from these robots on the gait dynamic stability. A knee exoskeleton and ankle assistive device (Robotic Shoe) are developed and used to provide walking assistance. The knee exoskeleton provides personalized knee joint assistive torque during the stance phase. The robotic shoe is a light-weighted mechanism that can store the potential energy at heel strike and release it by using an active locking mechanism at the terminal stance phase to provide push-up ankle torque and assist the toe-off. Lower-limb Kinematic time series data are collected for subjects wearing these devices in the passive and active mode. The changes of kinematics with and without these devices on lower-limb motion are first studied. Orbital stability, as one of the commonly used measure to quantify gait stability through calculating Floquet Multipliers (FM), is employed to asses the effects of these wearable devices on gait stability. It is shown that wearing the passive knee exoskeleton causes less orbitally stable gait for users, while the knee joint active assistance improves the orbital stability compared to passive mode. The robotic shoe only affects the targeted joint (right ankle) kinematics, and wearing the passive mechanism significantly increases the ankle joint FM values, which indicates less walking orbital stability. More analysis is done on a mechanically perturbed walking public data set, to show that orbital stability can quantify the effects of external mechanical perturbation on gait dynamic stability. This method can further be used as a control design tool to ensure gait stability for users of lower-limb assistive devices.Dissertation/ThesisMasters Thesis Mechanical Engineering 201

Exoskeleton-Mediated Physical Human-Human Interaction for a Sit-to-Stand Rehabilitation Task

Sit-to-Stand (StS) is a fundamental daily activity that can be challenging for stroke survivors due to strength, motor control, and proprioception deficits in their lower limbs. Existing therapies involve repetitive StS exercises, but these can be physically demanding for therapists while assistive devices may limit patient participation and hinder motor learning. To address these challenges, this work proposes the use of two lower-limb exoskeletons to mediate physical interaction between therapists and patients during a StS rehabilitative task. This approach offers several advantages, including improved therapist-patient interaction, safety enforcement, and performance quantification. The whole body control of the two exoskeletons transmits online feedback between the two users, but at the same time assists in movement and ensures balance, and thus helping subjects with greater difficulty. In this study we present the architecture of the framework, presenting and discussing some technical choices made in the design.Comment: 7 pages, 6 figures, submitted to 2024 IEEE The International Conference on Robotics and Automation (ICRA