63 citations · 65 across the 3 of their papers we have counts for
7 papers
A Sensorless Control System for an Implantable Heart Pump using a Real-time Deep Convolutional Neural Network
Masoud Fetanat, Michael Stevens, Christopher Hayward +1
Left ventricular assist devices (LVADs) are mechanical pumps, which can be used to support heart failure (HF) patients as bridge to transplant and destination therapy. To automatic…
Estimating Lower Body Kinematics using a Lie Group Constrained Extended Kalman Filter and Reduced IMU Count
Luke Wicent Sy, Nigel H. Lovell, Stephen J. Redmond
Goal: This paper presents an algorithm for estimating pelvis, thigh, shank, and foot kinematics during walking using only two or three wearable inertial sensors. Methods: The algor…
Estimating Lower Limb Kinematics using Distance Measurements with a Reduced Wearable Inertial Sensor Count
Luke Sy, Nigel H. Lovell, Stephen J. Redmond
This paper presents an algorithm that makes novel use of distance measurements alongside a constrained Kalman filter to accurately estimate pelvis, thigh, and shank kinematics for…
Advanced Intelligent Systems for Surgical Robotics
Mai Thanh Thai, Phuoc Thien Phan, Shing Wong +2
Surgical robots have had clinical use since the mid 1990s. Robot-assisted surgeries offer many benefits over the conventional approach including lower risk of infection and blood l…
Estimating Lower Limb Kinematics using a Lie Group Constrained EKF and a Reduced Wearable IMU Count
Luke Sy, Nigel H. Lovell, Stephen J. Redmond
This paper presents an algorithm that makes novel use of a Lie group representation of position and orientation alongside a constrained extended Kalman filter (CEKF) to accurately…
Estimating Lower Limb Kinematics using a Reduced Wearable Sensor Count
Luke Sy, Michael Raitor, Michael Del Rosario +4
Goal: This paper presents an algorithm for accurately estimating pelvis, thigh, and shank kinematics during walking using only three wearable inertial sensors. Methods: The algorit…