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

A Bipedal Mechanical Walker with Balancing Mechanism

Walkers are mechanical leg devices which perform motion similar to a physiological walk of animals or humans. They have many different usages among which the application for medical rehabilitation of injured persons not capable of walking is the most important. This paper presents the mechanism embedded in a mechanical walker by which the balancing of a human mass centre is accomplished. The benefit of such kind of mechanism is that a walker device with the balanced mass centre can be supplied with the feet of a smaller size. Moreover, it generates more pleasant walking movement, similar to the physiological bipedal motion. This mechanism has been calculated, 3D modelled and its operation simulated, analysed and numerically and graphically described. Finally, the motion of the chosen referent point on the mechanical walker obtained by the simulation is compared with the motion of the corresponding referent point on the human body acquired by camera. The results of this comparison disclosed that trajectories of the chosen referent points on the mechanical walker and human body are almost overlapped. Thus, it has been proven that the mechanism proposed in this paper is capable to balance the mass centre of a human body correctly

A Bipedal Mechanical Walker with Balancing Mechanism

Walkers are mechanical leg devices which perform motion similar to a physiological walk of animals or humans. They have many different usages among which the application for medical rehabilitation of injured persons not capable of walking is the most important. This paper presents the mechanism embedded in a mechanical walker by which the balancing of a human mass centre is accomplished. The benefit of such kind of mechanism is that a walker device with the balanced mass centre can be supplied with the feet of a smaller size. Moreover, it generates more pleasant walking movement, similar to the physiological bipedal motion. This mechanism has been calculated, 3D modelled and its operation simulated, analysed and numerically and graphically described. Finally, the motion of the chosen referent point on the mechanical walker obtained by the simulation is compared with the motion of the corresponding referent point on the human body acquired by camera. The results of this comparison disclosed that trajectories of the chosen referent points on the mechanical walker and human body are almost overlapped. Thus, it has been proven that the mechanism proposed in this paper is capable to balance the mass centre of a human body correctly

A Monocular Marker-Free Gait Measurement System

This paper presents a new, user-friendly, portable motion capture and gait analysis system for capturing and analyzing human gait, designed as a telemedicine tool to monitor remotely the progress of patients through treatment. The system requires minimal user input and simple single-camera filming (which can be acquired from a basic webcam) making it very accessible to nontechnical, nonclinical personnel. This system can allow gait studies to acquire a much larger data set and allow trained gait analysts to focus their skills on the interpretation phase of gait analysis. The design uses a novel motion capture method derived from spatiotemporal segmentation and model-based tracking. Testing is performed on four monocular, sagittal-view, sample gait videos. Results of modeling, tracking, and analysis stages are presented with standard gait graphs and parameters compared to manually acquired data

Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation

This paper introduces a newly developed gait rehabilitation device. The device, called LOPES, combines a freely translatable and 2-D-actuated pelvis segment with a leg exoskeleton containing three actuated rotational joints: two at the hip and one at the knee. The joints are impedance controlled to allow bidirectional mechanical interaction between the robot and the training subject. Evaluation measurements show that the device allows both a "pa- tient-in-charge" and "robot-in-charge" mode, in which the robot is controlled either to follow or to guide a patient, respectively. Electromyography (EMG) measurements (one subject) on eight important leg muscles, show that free walking in the device strongly resembles free treadmill walking; an indication that the device can offer task-specific gait training. The possibilities and limitations to using the device as gait measurement tool are also shown at the moment position measurements are not accurate enough for inverse-dynamical gait analysis

Extraction of bodily features for gait recognition and gait attractiveness evaluation

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-012-1319-2. Copyright @ 2012 Springer.Although there has been much previous research on which bodily features are most important in gait analysis, the questions of which features should be extracted from gait, and why these features in particular should be extracted, have not been convincingly answered. The primary goal of the study reported here was to take an analytical approach to answering these questions, in the context of identifying the features that are most important for gait recognition and gait attractiveness evaluation. Using precise 3D gait motion data obtained from motion capture, we analyzed the relative motions from different body segments to a root marker (located on the lower back) of 30 males by the fixed root method, and compared them with the original motions without fixing root. Some particular features were obtained by principal component analysis (PCA). The left lower arm, lower legs and hips were identified as important features for gait recognition. For gait attractiveness evaluation, the lower legs were recognized as important features.Dorothy Hodgkin Postgraduate Award and HEFCE

Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject's self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot-ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject's walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject's walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject's walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations

Markerless gait analysis vision system for real-time gait monitoring

On this paper a vision-based contact and markerless method for gait evaluation is proposed, and validated in different experimental setups against commercial motion capture systems (Vicon) and inertial gait analysis tools (GaitShoes). While the development goal is its integration on the ASBGo Smart Walker platform, only an inexpensive depth camera is required. It is shown to have reasonable results when computing gait metrics in real time, in different experimental setups, from different walker types, vision hardware and walking scenarios. Performance is evaluated through RMSD values for several gait metrics. Results illustrate that the proposed approach can be a valuable non-invasive, contactless and low cost alternative to gait analysis systems used in clinical rehabilitation environments.This work has been supported by the FEDER Funds through COMPETE 2020 — Programa Operacional Competitividade e Internacionalizacão (POCI) and P2020 with the Reference Project EML under Grant POCI-01-0247-FEDER-033067; COMPETE 2020 — Programa Operacional Competitividade e Internacionalizacão (POCI) with the Reference Project under Grant POCI-01-0145-FEDER-006941

Rhythmic Haptic Cueing Using Wearable Devices as Physiotherapy for Huntington Disease: Case Study

Background: Huntington disease (HD) is an inherited genetic disorder that results in the death of brain cells. HD symptoms generally start with subtle changes in mood and mental abilities; they then degenerate progressively, ensuing a general lack of coordination and an unsteady gait, ultimately resulting in death. There is currently no cure for HD. Walking cued by an external, usually auditory, rhythm has been shown to steady gait and help with movement coordination in other neurological conditions. More recently, work with other neurological conditions has demonstrated that haptic (ie, tactile) rhythmic cues, as opposed to audio cues, offer similar improvements when walking. An added benefit is that less intrusive, more private cues are delivered by a wearable device that leaves the ears free for conversation, situation awareness, and safety. This paper presents a case study where rhythmic haptic cueing (RHC) was applied to one person with HD. The case study has two elements: the gait data we collected from our wearable devices and the comments we received from a group of highly trained expert physiotherapists and specialists in HD. Objective: The objective of this case study was to investigate whether RHC can be applied to improve gait coordination and limb control in people living with HD. While not offering a cure, therapeutic outcomes may delay the onset or severity of symptoms, with the potential to improve and prolong quality of life. Methods: The approach adopted for this study includes two elements, one quantitative and one qualitative. The first is a repeated-measures design with three conditions: before haptic rhythm (ie, baseline), with haptic rhythm, and after exposure to haptic rhythm. The second element is an in-depth interview with physiotherapists observing the session. Results: In comparison to the baseline, the physiotherapists noted a number of improvements to the participant’s kinematics during her walk with the haptic cues. These improvements continued in the after-cue condition, indicating some lasting effects. The quantitative data obtained support the physiotherapists’ observations. Conclusions: The findings from this small case study, with a single participant, suggest that a haptic metronomic rhythm may have immediate, potentially therapeutic benefits for the walking kinematics of people living with HD and warrants further investigation

Biomechanics

Biomechanics is a vast discipline within the field of Biomedical Engineering. It explores the underlying mechanics of how biological and physiological systems move. It encompasses important clinical applications to address questions related to medicine using engineering mechanics principles. Biomechanics includes interdisciplinary concepts from engineers, physicians, therapists, biologists, physicists, and mathematicians. Through their collaborative efforts, biomechanics research is ever changing and expanding, explaining new mechanisms and principles for dynamic human systems. Biomechanics is used to describe how the human body moves, walks, and breathes, in addition to how it responds to injury and rehabilitation. Advanced biomechanical modeling methods, such as inverse dynamics, finite element analysis, and musculoskeletal modeling are used to simulate and investigate human situations in regard to movement and injury. Biomechanical technologies are progressing to answer contemporary medical questions. The future of biomechanics is dependent on interdisciplinary research efforts and the education of tomorrow’s scientists