Dr Tecla Bonci
PhD CEng FHEA
School of Mechanical, Aerospace and Civil Engineering
Lecturer in Biomechanics
t.bonci@sheffield.ac.uk
Room F111d, F floor, Sir Frederick Mappin Building (Broad Lane Building)
Full contact details
Dr Tecla Bonci
School of Mechanical, Aerospace and Civil Engineering
Room F111d, F floor
Sir Frederick Mappin Building (Broad Lane Building)
Mappin Street
Sheffield
S1 3JD
School of Mechanical, Aerospace and Civil Engineering
Room F111d, F floor
Sir Frederick Mappin Building (Broad Lane Building)
Mappin Street
Sheffield
S1 3JD
- Profile
-
I am a Lecturer in Biomechanics in the School of Mechanical, Aerospace and Civil Engineering (MAC) and in the Insigneo Institute at the University of Sheffield. I am Fellow of the Higher Education Academy and an IMechE member.After obtaining my undergraduate (BEng) and postgraduate (MEng) degrees from the Università Politecnica delle Marche (Ancona, Italy) in Biomedical Engineering, I received my PhD in Bioengineering as a joint cotutelle between the Alma Mater Studiorum – Università di Bologna and the University of Lyon under the supervision of Prof. Aurelio Cappozzo and Prof. Laurence Chèze (“The reconstruction of skeletal movement: the soft tissue artefact issue”). I held postdoctoral positions at the University of Rome “Foro italico” and at the Università degli Studi di Sassari working on human movement-related projects. Then I joined Aston University as a Teaching Fellow where I was module leader of three subjects (Biomechanics, Biomaterials, and Kinematics and Prosthetics) within the Biomedical Engineering BEng and MEng courses. At Aston, I managed the motion capture laboratory, co-supervised a PhD student and established an independent collaboration with the University of Sassari. Before being promoted to my lecturer position, I joined the University of Sheffield in 2019 as a Research Associate to work with Prof. Claudia Mazzà and exploit the unique opportunity to join Mobilise-D, one of the most important international partnership projects in the field of mobility monitoring. I am currently the Communications Committee lead within BioMedEng ECR Working Group.Since my PhD studies, my research interest has focused on measuring and modelling human movement. My research interest spans from increasing the resolution of human movement analysis, performed using either wearable devices or stereophotogrammetry, to advancing state of the art techniques to measure and understand real-world gait and mobility. This will enable addressing highly relevant clinical questions, such as objective disease progression, with a special focus on neurodegenerative diseases.
- Research interests
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- Digital Health
- Wearable Technology
- Digital Outcomes
- Biomedical Engineering
- Neurodegenerative diseases
- Ageing
- Biomedical signal processing
- Human movement analysis
- Stereophotogrammetry
- Soft tissue artefact/soft tissue deformation
- Modelling
- Publications
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Journal articles
- Discriminating between indoor and outdoor environments during daily living activities using local magnetic field characteristics and machine learning techniques.. IEEE Sensors Journal, 1-1.
- Real-world gait detection using a wrist-worn inertial sensor: validation study. JMIR Formative Research, 8. View this article in WRRO
- Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device. Scientific Reports, 14(1). View this article in WRRO
- Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases. Frontiers in Neurology, 14. View this article in WRRO
- Laboratory and free-living gait performance in adults with COPD and healthy controls. ERJ Open Research, 9(5). View this article in WRRO
- A single-sensor approach to quantify gait in patients with hereditary spastic paraplegia. Sensors, 23(14). View this article in WRRO
- Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium. Journal of NeuroEngineering and Rehabilitation, 20. View this article in WRRO
- A multi-sensor wearable system for the assessment of diseased gait in real-world conditions. Frontiers in Bioengineering and Biotechnology, 11.
- Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization. Scientific Data, 10. View this article in WRRO
- Design and validation of a multi-task, multi-context protocol for real-world gait simulation. Journal of NeuroEngineering and Rehabilitation, 19. View this article in WRRO
- Performance of a multi-sensor wearable system for validating gait assessment: preliminary results on patients and healthy. Gait & Posture, 97, 13-13.
- A deep learning model to discern indoor from outdoor environments based on data recorded by a tri-axial digital magnetic sensor. Gait & Posture, 97, 5-5.
- An algorithm for accurate marker-based gait event detection in healthy and pathological populations during complex motor tasks. Frontiers in Bioengineering and Biotechnology, 10.
- Characterisation of the transient mechanical response and the electromyographical activation of lower leg muscles in whole body vibration training. Scientific Reports, 12(1).
- A quality control check to ensure comparability of stereophotogrammetric data between session and systems. Sensors, 21(24). View this article in WRRO
- Technical validation of real-world monitoring of gait : a multicentric observational study. BMJ Open, 11(12). View this article in WRRO
- A method for gait events detection based on low spatial resolution pressure insoles data. Journal of Biomechanics, 127. View this article in WRRO
- Algorithms for walking speed estimation using a lower-back-worn inertial sensor: A cross-validation on speed ranges. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 1955-1964. View this article in WRRO
- Dynamic analysis of lower leg muscles response to whole body vibration stimulation at different frequencies and postures: implications for training.
- A multifactorial model of multiple sclerosis gait and its changes across different disability levels. IEEE Transactions on Biomedical Engineering, 68(11), 3196-3204. View this article in WRRO
- An objective methodology for the selection of a device for continuous mobility assessment. Sensors, 20(22). View this article in WRRO
- A joint kinematics driven model of the pelvic soft tissue artefact. Journal of Biomechanics, 111, 109998-109998.
- An augmented reality based platform to measure gaze and gait. Gait & Posture, 66, S6-S6.
- A comparative accuracy analysis of five sensor fusion algorithms for orientation estimation using magnetic and inertial sensors. Gait & Posture, 66, S9-S10.
- Standardization proposal of soft tissue artefact description for data sharing in human motion measurements. Journal of Biomechanics, 62, 5-13.
- Soft tissue displacement over pelvic anatomical landmarks during 3-D hip movements. Journal of Biomechanics, 62, 14-20.
- Whole Body Vibration Treatments in Postmenopausal Women Can Improve Bone Mineral Density: Results of a Stimulus Focussed Meta-Analysis. PLOS ONE, 11(12).
- Pelvis soft tissue artefact assessment during 3-D hip movements. Gait & Posture, 42, S36-S37.
- Rigid and non-rigid geometrical transformations of a marker-cluster and their impact on bone-pose estimation. Journal of Biomechanics, 48(15), 4166-4172.
- A model of the soft tissue artefact rigid component. Journal of Biomechanics, 48(10), 1752-1759.
- What Portion of the Soft Tissue Artefact Requires Compensation When Estimating Joint Kinematics?. Journal of Biomechanical Engineering, 137(6).
- A qualitative analysis of soft tissue artefact during running. Computer Methods in Biomechanics and Biomedical Engineering, 17(sup1), 124-125.
- Generation of realistic thigh soft tissue artefacts as a function of hip and knee kinematics. Gait & Posture, 39, S72-S73.
- A soft tissue artefact model driven by proximal and distal joint kinematics. Journal of Biomechanics, 47(10), 2354-2361.
- Generalized mathematical representation of the soft tissue artefact. Journal of Biomechanics, 47(2), 476-481.
- Muscle fatigue during elbow flexion-extension. Gait & Posture, 35, S32-S33.
- Author Correction: Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device. Scientific Reports, 14(1).
- Correction: Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium. Journal of NeuroEngineering and Rehabilitation, 21(1).
- A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings. Medical & Biological Engineering & Computing.
Conference proceedings papers
- Reliability of real-world walking activity and gait assessment in people with COPD. How many hours and days are needed?. M-Health/e-health (pp PA791-PA791)
- Predicting Disease Severity using Novel Digital Mobility Outcomes: A Deep Learning Approach in COPD Patients. M-Health/e-health (pp OA2765-OA2765)
- Laboratory and free-living gait performance in adults with COPD and healthy controls. M-Health/e-health (pp OA3185-OA3185)
- Impact of symptoms and disease severity on digital mobility outcomes in COPD. M-Health/e-health (pp PA1592-PA1592)
- From high-resolution time series to a single, clinically-interpretable value - considerations for the aggregation of real world walking speed assessed by wearable sensors in patients with chronic obstructive pulmonary disease (COPD). M-Health/e-health (pp PA1595-PA1595)
- A wearable multi-sensor system for real world gait analysis. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp 7020-7023). Virtual conference, 1 November 2021 - 1 November 2021. View this article in WRRO
- Can gait modelling predict disease progression in ms? A study using small body worn sensors in a clincial setting. MULTIPLE SCLEROSIS JOURNAL, Vol. 26(3_SUPPL) (pp 135-135)
- A novel multi-sensor system for gait assessment in real-world conditions: preliminary results. Convegno Nazionale di Bioingegneria (pp 472-475)
Preprints
- Co-creating the visualisation of digital mobility outcomes: a Delphi-process with patients. (Preprint), JMIR Publications Inc..
- Discriminating between indoor and outdoor environments during daily living activities using local magnetic field characteristics and machine learning techniques, Research Square Platform LLC.
- Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study (Preprint), JMIR Publications Inc..
- Estimating real-world walking speed from a single wearable device: analytical pipeline, results and lessons learnt from the Mobilise-D technical validation study, Research Square Platform LLC.
- A multi-sensor wearable system for gait assessment in real-world conditions: performance in individuals with impaired mobility, Research Square Platform LLC.
- Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium, Research Square Platform LLC.
- Design and validation of a multi-task, multi-phase protocol for real-world gait simulation, Research Square Platform LLC.
- Vibration Attenuation Via Mean of Lower Limb Muscles Occurs During Whole Body Vibrations And Differs Across Frequencies And Postures, Research Square Platform LLC.
- Discriminating between indoor and outdoor environments during daily living activities using local magnetic field characteristics and machine learning techniques.. IEEE Sensors Journal, 1-1.
- Teaching interests
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BIE6436 – Human Movement Biomechanics