123 citations · 249 across the 9 of their papers we have counts for
9 papers
First International StepUP Competition for Biometric Footstep Recognition: Methods, Results and Remaining Challenges
Robyn Larracy, Eve MacDonald, Angkoon Phinyomark +5
Biometric footstep recognition, based on a person's unique pressure patterns under their feet during walking, is an emerging field with growing applications in security and safety.…
A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds
Robyn Larracy, Angkoon Phinyomark, Ala Salehi +5
Gait refers to the patterns of limb movement generated during walking, which are unique to each individual due to both physical and behavioral traits. Walking patterns have been wi…
Analyzing the Impact of Class Transitions on the Design of Pattern Recognition-based Myoelectric Control Schemes
Shriram Tallam Puranam Raghu, Dawn T. MacIsaac, Erik J. Scheme
Despite continued efforts to improve classification accuracy, it has been reported that offline accuracy is a poor indicator of the usability of pattern recognition-based myoelectr…
A Framework and Call to Action for the Future Development of EMG-Based Input in HCI
Ethan Eddy, Erik Scheme, Scott Bateman
Electromyography (EMG) has been explored as an HCI input modality following a long history of success for prosthesis control. While EMG has the potential to address a range of hand…
A Comparison of Amputee and Able-Bodied Inter-Subject Variability in Myoelectric Control
Evan Campbell, Jason Chang, Angkoon Phinyomark +1
Despite decades of research and development of pattern recognition approaches, the clinical usability of myoelectriccontrolled prostheses is still limited. One of the main issues i…
Differences in Perspective on Inertial Measurement Unit Sensor Integration in Myoelectric Control
Evan Campbell, Angkoon Phinyomark, Erik Scheme
Recent human computer-interaction (HCI) studies using electromyography (EMG) and inertial measurement units (IMUs) for upper-limb gesture recognition have claimed that inertial mea…
Unsupervised Domain Adversarial Self-Calibration for Electromyographic-based Gesture Recognition
Ulysse Côté-Allard, Gabriel Gagnon-Turcotte, Angkoon Phinyomark +4
Surface electromyography (sEMG) provides an intuitive and non-invasive interface from which to control machines. However, preserving the myoelectric control system's performance ov…
A Transferable Adaptive Domain Adversarial Neural Network for Virtual Reality Augmented EMG-Based Gesture Recognition
Ulysse Côté-Allard, Gabriel Gagnon-Turcotte, Angkoon Phinyomark +4
Within the field of electromyography-based (EMG) gesture recognition, disparities exist between the offline accuracy reported in the literature and the real-time usability of a cla…
Interpreting Deep Learning Features for Myoelectric Control: A Comparison with Handcrafted Features
Ulysse Côté-Allard, Evan Campbell, Angkoon Phinyomark +3
The research in myoelectric control systems primarily focuses on extracting discriminative representations from the electromyographic (EMG) signal by designing handcrafted features…