Arash Arami

University of Waterloo | UWaterloo · Department of Mechanical and Mechatronics Engineering

Accurate interaction force estimation can play an important role in optimization human-robot interaction in exoskeleton. In this work, we propose a novel approach for system identification of exoskeleton dynamics in presence of interaction forces as a whole multi-body system regardless of gait phase or any assumption on human-exoskeleton interactio...

Inverse dynamics is a common tool for determining human joint torques during walking. The traditional approaches rely on ground reaction force and kinematics measurements prior to analysis. A novel real-time hybrid method is proposed in this work by integrating a neural network and dynamic model that only requires kinematic data. An end-to-end neur...

An ultra-robust accurate gait phase estimator is developed by training a time-delay neural network (D67) on data collected from the hip and knee joint angles of 14 participants walking on a treadmill and overground. Collected data include normal gait at speeds ranging from 0.1m/s to 1.9m/s and conditions such as long stride, short stride, asymmetri...

Objective: To develop and evaluate an accurate method for cuffless blood pressure (BP) estimation during moderate- and heavy-intensity exercise. Methods: Twelve participants performed three cycling exercises: a ramp-incremental exercise to exhaustion, and moderate and heavy pseudorandom binary sequence exercises on an electronically braked cycle...

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on s...

Virtual Energy Regulator (VER) is a time independent controller that can generate stable limit cycles in lower-limb exoskeleton devices. In this work, we apply VER to control a lower-limb exoskeleton for assistive walking. We design two different limit cycles for hip and knee joints to assist the user during overground walking with the Indego explo...

An accurate real-time gait phase estimator for normal and asymmetric gait is developed by training and testing a time-delay neural network on gait data collected from six participants during treadmill walking. The trained model can generate smooth and highly accurate predictions of the gait phase with a root mean square error of less than 3.48% and...

An efficient inverse optimal control method named Adaptive Reference IOC is introduced to study natural walking with musculoskeletal models. Adaptive Reference IOC utilizes efficient inner-loop direct collocation for optimal trajectory prediction along with a gradient-based weight update inspired by structured classification in the outer-loop to ac...

A substantial barrier to the clinical adoption of cuffless blood pressure (BP) monitoring techniques is the lack of unified error standards and methods of estimating measurement uncertainty. This study proposes a fusion approach to improve accuracy and estimate prediction interval (PI) as a proxy for uncertainty for cuffless blood BP monitoring. BP...

This study examines how people learn to perform lower limb control in a novel task with a hoverboard requiring to maintain dynamic balance. We designed an experiment to investigate the learning of hoverboard balance and two control strategies: A hip strategy, which mainly uses hip movements to change the angle of the foot, and an ankle strategy rel...

Abstrat Closed-die cast-forging operations require a deliberate design of forging preforms (work-piece) to encourage process-related grain refinement and good metal flow during deformation. To this end, we propose a computational design framework and use artificial neural networks (ANNs) for generating and predicting the forging response of preform...

This paper presents a novel method for reference trajectory adaptation in lower limb rehabilitation exoskeletons during walking. Our adaptation rule is extracted from a cost function that penalizes both interaction force and trajectory modification. By adding trajectory modification term into the cost function, we restrict the boundaries of the ref...

In this paper, we present a novel adaptation rule to optimize the exoskeleton assistance in rehabilitation tasks. The proposed method adapts the exoskeleton contribution to user impairment severity without any prior knowledge about the user motor capacity. The proposed controller is a combination of an adaptive feedforward controller and a low gain...

In this paper, we introduce a novel control strategy called Virtual Energy Regulator (VER) for lower limb rehabilitation exoskeletons. Unlike the conventional trajectory tracking controllers, VER, which is a time-independent controller , does not control the exoskeleton joints over a reference trajectory. Instead, it imposes a constraint in the sta...

Every year, between 250,000 and 500,000 people suffer from Spinal Cord Injury (SCI) around the world. Functional electrical stimulation (FES) is one of the assistive approaches that is developed to facilitate motor function movement. Usually researchers employ the FES to enforce the muscular system of SCI individuals and enable them to move. Accord...

This paper presents a novel method for reference trajectory adaptation in lower limb rehabilitation exoskeletons during walking. Our adaptation rule is extracted from a cost function that penalizes both interaction force and trajectory modification. By adding trajectory modification term into the cost function, we restrict the boundaries of the ref...

Human gait optimality has been investigated recently, with the development of detailed musculoskeletal models, through trajectory optimization approaches or deep reinforcement learning (DRL). Trajectory optimization studies are limited by the trajectory length and can only generate open-loop solutions. While existing DRL solutions provide closed-lo...

The objective is to develop a cuffless method that accurately estimates blood pressure (BP) during activities of daily living. User-specific nonlinear autoregressive models with exogenous inputs (NARX) are implemented using artificial neural networks to estimate the BP waveforms from electrocardiography and photoplethysmography signals. To broaden...

The purpose of this data collection was for the validation of a cuffless blood pressure estimation model during activities of daily living. Data were collected on five young healthy individuals (four males, age 28 ± 6.6 yrs) of varied fitness levels, ranging from sedentary to regularly active, and free of cardiovascular and peripheral vascular dise...

Spasticity, a common symptom in patients with upper motor neuron lesions, reduces the ability of a person to freely move their limbs by generating unwanted reflexes. Spasticity can interfere with rehabilitation programs and cause pain, muscle atrophy and musculoskeletal deformities. Despite its prevalence, it is not commonly understood. Widely used...

This work presents a modelling approach to predict the blood pressure (BP) waveform time series during activities of daily living without the use of a traditional pressure cuff. A nonlinear autoregressive model with exogenous inputs (NARX) is implemented using artificial neural networks and trained to predict the BP waveform time series from electr...

Mechanical impedance, which changes with posture and muscle activations, characterizes how the central nervous system regulates the interaction with the environment. Traditional approaches to impedance estimation, based on averaging of movement kinetics, requires a large number of trials and may introduce bias to the estimation due to the high vari...

This paper presents a versatile cable-driven robotic interface to investigate the single-joint joint neuromechanics of the hip, knee and ankle in the sagittal plane. This endpoint-based interface offers highly dynamic interaction and accurate position control (as is typically required for neuromechanics identification), and provides measurements of...

Limb viscoelasticity is a critical factor used to regulate the interaction with the environment. It plays a key role in modelling human sensorimotor control, and can be used to assess the condition of healthy and neurologically affected individuals. This paper reports the estimation of hip joint viscoelasticity during voluntary force control using...

The objective is to develop a cuffless modelling approach to accurately estimate the blood pressure (BP) waveform and extract important BP features, such as the systolic BP (SBP), diastolic BP (DBP), and mean BP (MAP). Access to the full waveform has significant advantages over previous cuffless BP estimation tools in terms of accuracy and access t...

This work presents a modelling approach to accurately predict the blood pressure (BP) waveform time series from a single input signal. A nonlinear autoregressive model with exogenous input (NARX) is implemented using artificial neural networks and trained on Electrocardiography (ECG) signals to predict the BP waveform. The efficacy of the model is...

Limb viscoelasticity is a critical factor used to regulate the interaction with the environment. It plays a key role in modelling human sensorimotor control, and can be used to assess the condition of healthy and neurologically affected individuals. This paper reports the estimation of hip joint viscoelasticity during voluntary force control using...

This paper presents a versatile cable-driven robotic interface to investigate the single-joint joint neuromechanics of the hip, knee and ankle. This endpoint-based interface offers highly dynamic interaction and accurate position control, as is typically required for neuromechanics identification. It can be used with the subject upright, correspond...

This paper presents a novel technique to predict freezing of gait in advance-stage Parkinsonian patients using movement data from wearable sensors. A two-class approach is presented which consists of autoregressive predictive models to project the feature time series, followed by machine learning based classifiers to discriminate freezing from nonf...

Total shoulder arthroplasty is an effective treatment for glenohumeral osteoarthritis. However, it still suffers from a substantial rate of mechanical failure, which may be related to cyclic off-center loading of the humeral head on the glenoid. In this work, we present the design and evaluation of a glenohumeral joint robotic simulator developed t...

In this work, we investigate the potential of different feature families extracted from wearable inertial measurement units (IMUs) in real-time detection of freezing of gait (FOG) in Parkinson’s disease (PD). Two groups of features were extracted and analyzed. Group 1 comprised of spatiotemporal parameters of gait, while group 2 includes the time a...

In a stable bimanual trajectory tracing task with interlimb spatial and temporal synchrony, blocking the visual information from one hand may alter the performance of either hand. In this paper, we investigate the effect of visual information on motor behaviour of dominant and non-dominant hands during a bimanual task, with a focus on motor lateral...

Introduction: According to recent research in human motor control, the central nervous system (CNS) coordinates body motions by minimizing a physiological cost function that represents some performance criteria [1,2]. This work presents a novel method to determine the underlying cost function that can predict the movement of an upper limb subject t...

The main goal of the Symbitron project was to develop a safe, bio-inspired, personalized wearable exoskeleton that enables SCI patients to walk without additional assistance, by complementing their remaining motor function. Here we give an overview of major achievements of the projects.

Introduction: Excessive or eccentric glenohumeral (GH) translations can lead to serious complications within a prosthetic shoulder, such as GH instability or prosthetic loosening [1]. The aim of this study is therefore to design a robotic platform for the study of the GH translations. This robot did reproduce the simulated internal forces and orien...

Knee implant loosening is mainly caused by the weakness of the prosthesis-bone interface and is the main reason for surgical revisions. However, pre-operative diagnosis is difficult due to lack of accurate tests. In this study, we developed a vibration-based system to detect the loosening of the tibial implant of an instrumented knee prosthesis. Th...

A novel neuromechanical model for investigating patient-specific lower limb movement dynamics after spinal cord injury (SCI) is presented. The model is designed in joint space and takes into account muscle neuromechanics. Application of the model is demonstrated in the application of a balancing task.

This work presents a wearable device and the algorithms for quantitative modelling of joint spasticity and its application in a pilot group of subjects with different levels of spinal cord injury. The device comprises light-weight instrumented handles to measure the interaction force between the subject and the physical therapist performing the tes...

This work presents an accurate, robust, wearable measurement system for foot clearance estimation along with algorithms to provide a real-time estimate of foot height and orientation. Different configurations of infrared distance meter sensors were used, both alone and in combination with an inertial measurement unit. In order to accurately estimat...

Wearable devices to assist abnormal gaits require controllers that interact with the user in an intuitive and unobtrusive manner. To design such a controller, we investigated a bio-inspired walking controller for orthoses and prostheses. We present (i) a Simulink neuromuscular control library derived from a computational model of reflexive neuromus...

Here, we present a low-power magnetic measurement system based on only two Hall-effect elements and a permanent magnet integrated into a smart knee prosthesis to accurately measure knee flexion–extension. The smart prosthesis was tested in a robotic knee simulator that provides squat movements and different patterns of recorded gait from subjects....

Background: Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients' mobility in daily life. Physical activity performance in daily-life can be assessed using unobtrusive monitoring, for example with a single se...

Introduction Functional hallux limitus (Fhl) is a loss of 1st metatarsophalangeal joint extension during the second half of the single-support phase, when the weight-bearing foot is in maximal dorsiflexion, with important consequences during gait. Our objectives were to evaluate the functional results in the sagittal plane biomechanics following t...

In this work we present the implantable and wearable measurement system developed for smart knee prostheses monitoring. The kinematic measurement system contains three anisotropic magnetoresistive sensors embedded into the polyethylene part of the prostheses. The kinematic measurement system also has two inertial measurement units to be worn by the...

Total knee arthroplasty is a widely performed surgical technique. Soft tissue force balancing during the operation relies strongly on the experience of the surgeon in equilibrating tension in the collateral ligaments. Little information on the forces in the implanted prosthesis is available during surgery and post-operative treatment. This paper pr...

In this paper, we present a method for automated calibration of an implanted anisotropic magnetoresistive (AMR) sensor for measuring the internal-external rotation in a prosthetic knee without using any reference measurement. The measurement system consists of a permanent magnet and a 2-D AMR sensor configured and embedded into the prosthesis. Usin...

Ligament balance is an important and subjective task performed during total knee arthroplasty (TKA) procedure. For this reason, it is desirable to develop instruments to quantitatively assess the soft-tissue balance since excessive imbalance can accelerate prosthesis wear and lead to early surgical revision. The instrumented distractor proposed in...

Subject-specific modelling of Total Knee Arthroplasty could be an efficient method to preoperatively evaluate surgical options. In particular, the question of the necessity of patellar resurfacing is still a debatable issue. The aim of this work was to validate a numerical model of Total Knee Arthroplasty using an instrumented robotic knee simulato...

In this paper, we present a magnetic measurement system for integration into smart knee prostheses to accurately measure the combination of two knee rotations; namely flexion-extension (FE) and internal-external (IE) rotations. This measurement system consists of two permanent magnets inserted into the femoral and tibial parts of the prosthesis and...

In this work, we present the general concept of an instrumented smart knee prosthesis for in-vivo measurement of forces and kinematics. This system can be used for early monitoring of the patient after implantation and prevent possible damage to the prosthesis. The diagnosis of defects can be done by detecting the load imbalance or abnormal forces...

This paper describes the development of a polyimide-based MEMS strain-sensing device. Finite element analysis was used to investigate an artificial knee implant and assist on device design and to optimize sensing characteristics. The sensing element of the device was fabricated using polyimide micromachining with embedded thin-metallic wires and pl...

The recent advances in wearable inertial sensors opened a new horizon for pervasive measurement of human locomotion even in aquatic environment. In this paper we proposed an automatic approach of detecting the key temporal events of breaststroke swimming as a tentatively explored technique due to the complexity of the stroke. We used two inertial m...

In this work, we studied a combination of embedded magnetic measurement system in a knee prosthesis and wearable inertial sensors to estimate two knee joint rotations namely flexion-extension and internal-external rotations. The near optimal sensor configuration was designed for implantable measurement system, and linear estimators were used to est...

We propose a new minimal wearable system and a classifier for physical activity recognition. The configuration is solely based on two force sensors placed anteriorly and posteriorly under the feet. To find the optimal sensor configuration, we estimated the total force under the feet during daily activities. The estimation was based on a linear regr...

The paper presents an analogue front-end and ADC integrated circuit for processing signals of sensors implanted into joint prosthesis. The circuit is designed to be operated with Wheatstone bridge sensors, such as strain gauges, pressure, Hall Effect, magneto-resistive sensors, etc. It performs sensor supply multiplexing, sensor signal amplificatio...

In this work we tackled the problem of accurate measurement of internal-external (IE) rotations in the prosthetic knee. We presented a magnetic measurement system to be implanted in the knee prostheses in order to measure IE without soft tissue artifacts. The measurement system consisted of a permanent magnet attached under the tibial plate of the...

In this work we present an instrumented smart knee prosthesis for in-vivo measurement of forces and kinematics. Studying the constraints, we designed minimal sensory systems to be placed in the polyethylene part of the prosthesis. The magnetic sensors and a permanent magnet are chosen and configured to measure the relative kinematics of the prosthe...

Dealing with uncertainties and lack of knowledge about problems and situations, there is a perpetual difficulty to evaluate the situations and action values in all time steps. On the other hand, the design of critics which delicately guide the agent even with reinforcement rewards and punishments in these complicated or blurred environments is labo...