Publications by Kamiar Aminian

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Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

Gait speed is an important parameter to characterize people's daily mobility. For real-world speed measurement, inertial sensors or Global Navigation Satellite System (GNSS) can be used on wrist, possibly integrated in a wristwatch. However, power consumpt ...

In clinical settings, functional evaluation of shoulder movement is primarily based on what the patient thinks he/she is able to do rather than what he/she is actually performing. We proposed a new approach for shoulder assessment based on inertial sensors ...

A spring mass model is often used to describe human running, allowing to understand the concept of elastic energy storage and restitution. The stiffness of the spring is a key parameter and different methods have been developed to estimate both the vertica ...

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 prosthes ...

There is a lack of knowledge about the accuracy of the Conventional Gait Model (CGM), compared to the true bone motion. Accuracy is hindered by both marker misplacement and soft-tissue artefact (STA). The effect of the lateral knee marker (KNE) misplacemen ...

Various factors, such as fear of falling, postural instability, and altered executive function, contribute to the high risk of falling in Parkinson's disease (PD). Dual-task training is an established method to reduce this risk. Motor-perceptual task combi ...

Accurate assessment of Parkinson’s disease (PD) ON and OFF states in the usual environment is essential for tailoring optimal treatments. Wearables facilitate measurements of gait in novel and unsupervised environments; however, differences between unsuper ...

Children may suffer knee injuries due to motor vehicle crashes, sports, and falls. Additionally, children can suffer from rheumatic, neurological, musculoskeletal, and neuromuscular disorders which restrict joint movement. These types of injuries and disor ...

Introduction: The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in natur ...

This study aimed to investigate the influence of ankle osteoarthritis (AOA) treatments, i.e., ankle arthrodesis (AA) and total ankle replacement (TAR), on the kinematics of multi-segment foot and ankle complex during relatively long-distance gait.Forty-five subjects in four groups (AOA, AA, TAR, and control) were equipped with a wearable system consisting of inertial sensors installed on the tibia, calcaneus, and medial metatarsals. The subjects walked 50-m twice while the system measured the kinematic para

Measurement of the energy expenditure is crucial to understand the biophysics of any kind of human locomotion. Despite the promising application of inertial measurement unit (IMU) for quantification of the energy expenditure during human on-land activities ...

Thanks to decades of research, gait analysis has become an efficient tool. However, mainly due to the price of the motion capture systems, standard gait laboratories have the capability to measure only a few consecutive steps of ground walking. Recently, w ...

Background and aims. Falls among older people remain a major public health challenge. Body-worn sensors are needed to improve the understanding of the underlying mechanisms and kinematics of falls. The aim of this systematic review is to assemble, extract ...

Although many methods have been developed to detect walking by using body-worn inertial sensors, their performances decline when gait patterns become abnormal, as seen in children with cerebral palsy (CP). The aim of this study was to evaluate if fine-tuni ...

The choice of input image size can have a significant impact on the performance of the state-of-the-art algorithms. We can always customize the algorithms by training and fine-tuning them on our datasets, but it is time consuming. Nowadays there is a trend ...

Animal‐borne accelerometers have been used across more than 120 species to infer biologically significant information such as energy expenditure and broad behavioural categories. While the accelerometer’s high sensitivity to movement and fast response time ...

Introduction Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measuremen ...

This study proposes a new robust classifier for sit-to-stand (SiSt) and stand-to-sit (StSt) detection in daily activity. The monitoring system consists of a single inertial sensor placed on the trunk. By using dynamic time warping, the trunk acceleration p ...

In this work, a magnetic measurement system was designed and tested to estimate the Internal-External rotation between the Tibial and Femural parts of a knee prosthesis. To obtain this, the sensors were inserted in polyethylene part while a permanent magne ...

Kamiar Aminian

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Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

Real-world gait speed estimation using wrist sensor: A personalized approach

Distribution of arm velocity and frequency of arm usage during daily activity: objective outcome evaluation after shoulder surgery

Vertical and Leg Stiffness Modeling During Running: Effect of Speed and Incline

Implantable and wearable measurement system for smart knee prosthesis

On the accuracy of the Conventional gait Model: Distinction between marker misplacement and soft tissue artefact errors

Dual-Task Treadmill Training for the Prevention of Falls in Parkinson's Disease: Rationale and Study Design

Comparison of Laboratory and Daily-Life Gait Speed Assessment during ON and OFF States in Parkinson’s Disease

Normative Knee Range of Motion for Children

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

Multi-segment foot kinematics after total ankle replacement and ankle arthrodesis during relatively long-distance gait

Estimation of Front-Crawl Energy Expenditure Using Wearable Inertial Measurement Units

Evaluation of a mixed approach combining stationary and wearable systems to monitor gait over long distance

Fall detection with body-worn sensors A systematic review

A Personalized Approach to Improve Walking Detection in Real-Life Settings: Application to Children with Cerebral Palsy

Enhancing Hand and Object Detection for Monitoring Patients with Upper-Limb Impairment: A Study on the Impact of Input Size in Foundation Models

Seek and learn: Automated identification of microevents in animal behaviour using envelopes of acceleration data and machine learning

Technical validation of real-world monitoring of gait: a multicentric observational study

Detection and Classification of Postural Transitions in Real-World Conditions

A new method for internal-external rotation measurement in a prosthetic knee