Faculty profile
Jonathan Kofman
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Research
Latest papers
Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.
Sensors (Basel, Switzerland) · 2024
Prediction of Freezing of Gait in Parkinson's Disease Using Unilateral and Bilateral Plantar-Pressure Data.
Frontiers in neurology · 2022
Prediction and detection of freezing of gait in Parkinson's disease from plantar pressure data using long short-term memory neural-networks.
Journal of neuroengineering and rehabilitation · 2021 · senior author
Latest funding
- $81,000
3D Imaging for Uncontrolled and Dynamic Conditions and Mobile and Wearable 3D Sensing
NSERC · 2022 · Principal investigator
- $104,944
Lower-limb wearable exoskeleton system to advance assisted mobility research
NSERC · 2018 · Co-investigator
- $25,000
Vision-based 3D inspection of automotive seats
NSERC · 2018 · Principal investigator
18 publications.
Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.
Pardoel S, AlAkhras A, Jafari E, Kofman J, Lemaire ED, Nantel J
Prediction of Freezing of Gait in Parkinson's Disease Using Unilateral and Bilateral Plantar-Pressure Data.
Pardoel S, Nantel J, Kofman J, Lemaire ED
Prediction and detection of freezing of gait in Parkinson's disease from plantar pressure data using long short-term memory neural-networks.
Shalin G, Pardoel S, Lemaire ED, Nantel J, Kofman J
Grouping successive freezing of gait episodes has neutral to detrimental effect on freeze detection and prediction in Parkinson's disease.
Pardoel S, Shalin G, Lemaire ED, Kofman J, Nantel J
Early Detection of Freezing of Gait during Walking Using Inertial Measurement Unit and Plantar Pressure Distribution Data.
Pardoel S, Shalin G, Nantel J, Lemaire ED, Kofman J
Wearable-Sensor-based Detection and Prediction of Freezing of Gait in Parkinson's Disease: A Review.
Pardoel S, Kofman J, Nantel J, Lemaire ED
Dual-Task Elderly Gait of Prospective Fallers and Non-Fallers: A Wearable-Sensor Based Analysis.
Howcroft J, Lemaire ED, Kofman J, McIlroy WE
Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.
Drover D, Howcroft J, Kofman J, Lemaire ED
Feature selection for elderly faller classification based on wearable sensors.
Howcroft J, Kofman J, Lemaire ED
Elderly fall risk prediction using static posturography.
Howcroft J, Lemaire ED, Kofman J, McIlroy WE
3D Imaging for Uncontrolled and Dynamic Conditions and Mobile and Wearable 3D Sensing
Principal investigators: Kofman, Jonathan
Keywords: 3d imaging; 3d shape measurement; fringe projection; computer vision; robot grasping; human assistive systems; prosthetic-hand grasping
Lower-limb wearable exoskeleton system to advance assisted mobility research
Principal investigators: Tung, James
Vision-based 3D inspection of automotive seats
Principal investigators: Kofman, Jonathan
PACKAGING AND CHARACTERIZATION FACILITY FOR HIGH SPEED X-RAY DETECTORS
Principal investigators: Karim, KarimSallaudin
3D Imaging for Uncontrolled Conditions and Mobile and Wearable 3D Sensing
Principal investigators: Kofman, Jonathan
Intelligent Sensors, Devices, and Systems
Principal investigators: Kofman, Jonathan
Vision-based 3D shape and volume sensing of deformable surfaces
Principal investigators: Kofman, Jonathan
Fast high resolution 3D imaging for body surface shape measurement
Principal investigators: Kofman, Jonathan
Intelligent human-assistive devices, sensors, and systems
Principal investigators: Kofman, Jonathan
Three-dimensional (3D) full-field imaging system
Principal investigators: Kofman, Jonathan
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Julie Nantel and Jonathan Kofman: 6 shared papers
- Cynthia Kendell and Jonathan Kofman: 1 shared paper
- Systems Design Engineering
- Human Kinetics
- Medicine
Co-authors at University of Waterloo, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
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