A5043385815- Musculoskeletal pain and rehabilitation
- Spine and Intervertebral Disc Pathology
- Muscle activation and electromyography studies
- Sports injuries and prevention
- Sports Performance and Training
- Lower Extremity Biomechanics and Pathologies
- Prosthetics and Rehabilitation Robotics
- Shoulder Injury and Treatment
- Scoliosis diagnosis and treatment
- Osteoarthritis Treatment and Mechanisms
- Stroke Rehabilitation and Recovery
- Advanced Sensor and Energy Harvesting Materials
- Spinal Fractures and Fixation Techniques
- Medical Imaging and Analysis
- Total Knee Arthroplasty Outcomes
- Occupational Health and Performance
- Balance, Gait, and Falls Prevention
- Hip disorders and treatments
- Anesthesia and Pain Management
- Myofascial pain diagnosis and treatment
- Pain Management and Placebo Effect
- Clinical practice guidelines implementation
- Bone fractures and treatments
- Voice and Speech Disorders
- Physical Activity and Health
Imperial College London
2016-2025
Charing Cross Hospital
2013-2023
Royal Marsden Hospital
2023
Imperial College Healthcare NHS Trust
2020-2023
Royal Ottawa Mental Health Centre
2023
Royal British Legion
2021
University of Strathclyde
2021
Arthur M. Sackler Gallery
2020
National Health Service
2020
Employment Agency
2015
<b>SUMMARY:</b> Posterior reversible encephalopathy syndrome (PRES) is a neurotoxic state accompanied by unique brain imaging pattern typically associated with number of complex clinical conditions including: preeclampsia/eclampsia, allogeneic bone marrow transplantation, solid organ autoimmune diseases and high dose cancer chemotherapy. The mechanism behind the developing vasogenic edema CT or MR appearance PRES not known. Two theories have historically been proposed: 1) Severe hypertension...
Low back pain (LBP) is a significant health problem worldwide, with lifetime prevalence of 84% in the general adult population. To rationalise management LBP, clinical practice guidelines (CPGs) have been issued various countries around world. This study aims to identify and compare recommendations recent CPGs for LBP across
There has been a rising interest in wearable and implantable biomedical sensors over the last decade. However, many technologies have not integrated into clinical care, due to limited understanding of user-centered design issues. Little information is available about these issues there need adopt more rigorous evidence standards for features allow important medical progress quicker care. Current trends patient preferences be incorporated at an early stage process prospective sensors. The...
Background With the rapid development of mobile health (mHealth) technology, many apps have been introduced to commercial market for people with back pain conditions. However, little is known about their content, quality, approaches care low (LBP), and associated risks use. Objective The aims this research were (1) identify self-management LBP currently on (2) assess intervention theoretical approaches, risk-related approaches. Methods UK iTunes Google Play stores initially searched related...
This study was designed to investigate corticospinal excitability of lumbar muscles using transcranial magnetic stimulation (TMS) in patients with chronic low back pain and correlate this self-rated measures disability pain.Twenty-four 11 healthy control subjects were used study. TMS delivered through an angled double-cone coil, its cross-over on the vertex a posterior-to-anterior current flow brain. Electromyographic (EMG) recordings made from erector spinae (ES) at fourth level. Motor...
Gait adaptations in people with severe knee osteoarthritis (OA) have been well documented, increased adduction moments (KAM) the most commonly reported parameter. Neuromuscular also reported, including reduced postural control. However these may be result of morphological changes joint, rather than cause. This study aimed to determine if early OA altered gait parameters and neuromuscular adaptations. tasks were performed by 18 medial age gender-matched control subjects. Parameters measured...
This paper tackles the problem of automatic detection knee osteoarthritis. A computer system is built that takes as input body kinetics and produces output not only an estimation presence osteoarthritis, previously done in literature, but also most discriminating parameters along with a set rules on how this decision was reached. fills gap interpretability between medical engineering approaches. We collected locomotion data from 47 subjects osteoarthritis healthy subjects. Osteoarthritis...
Gait analysis is an important clinical tool. A variety of models are used for gait analysis, each yielding different results. Errors in model outputs can occur due to inaccurate marker placement and skin motion artefacts, which may be reduced using a cluster-based model. We aimed compare custom-made cluster (ClusBB) with Vicon's plug-in gait. total 21 healthy subjects wore sets the ClusBB simultaneously while walking on 6-m walkway. Marker force plate data were captured synchronously joint...
The prevalence of osteoarthritis is increasing globally but current compliance with rehabilitation remains poor. This study explores whether wearable sensors can be used to provide objective measures performance a view using them as motivators aid rehabilitation. More specifically, the use novel attachable sensor integrated into clothing and inertial measurement units located in two different positions, at waist thigh pocket, was investigated. Fourteen healthy volunteers were asked complete...
We introduce a novel magnetic angular rate gravity (MARG) sensor fusion algorithm for inertial measurement. The new improves the popular gradient descent (ʻMadgwick') increasing accuracy and robustness while preserving computational efficiency. Analytic experimental results demonstrate faster convergence multiple variations of through changing inclination. Furthermore, decoupling field variance from roll pitch estimation is proven enhanced robustness. validated in human-machine interface...
Musculoskeletal models permit the determination of internal forces acting during dynamic movement, which is clinically useful, but traditional methods may suffer from slowness and a need for extensive input data. Recently, there has been interest in use supervised learning to build approximate computationally demanding processes, with benefits speed flexibility. Here, we deep neural network learn mapping movement space muscle space. Trained on set kinematic, kinetic electromyographic...
Velostat is a low-cost, low-profile electrical bagging material with piezoresistive properties, making it an attractive option for in-socket pressure sensing. The focus of this research was to explore the suitability Velostat-based system providing real-time socket profiles. prototype performance explored through series bench tests determine properties including accuracy, repeatability and hysteresis responses, participant testing single subject. fabricated sensors demonstrated mean accuracy...
Deep learning biomechanical models perform optimally when trained with large datasets, however these can be challenging to collect in gait labs, while limited augmentation techniques are available. This study presents a data approach based on generative adversarial networks which generate synthetic motion capture (mocap) datasets of marker trajectories and ground reaction forces (GRFs). The proposed architecture, called autoencoder, consists an encoder compressing mocap latent vector,...