Publications

2024

1. Multimodal fusion of emg and vision for human grasp intent inference in prosthetic hand control

   Mehrshad Zandigohar ,  Mo Han ,  Mohammadreza Sharif , and 8 more authors

   Frontiers in Robotics and AI, 2024

2022

1. Inference of Upcoming Human Grasp Using EMG During Reach-to-Grasp Movement

   Mo Han ,  Mehrshad Zandigohar ,  Sezen Yagmur Günay , and 2 more authors

   Frontiers in Neuroscience, 2022

   Abs

   Electromyography (EMG) data has been extensively adopted as an intuitive interface for instructing human-robot collaboration. A major challenge to the real-time detection of human grasp intent is the identification of dynamic EMG from hand movements. Previous studies predominantly implemented the steady-state EMG classification with a small number of grasp patterns in dynamic situations, which are insufficient to generate differentiated control regarding the variation of muscular activity in practice. In order to better detect dynamic movements, more EMG variability could be integrated into the model. However, only limited research was conducted on such detection of dynamic grasp motions, and most existing assessments on non-static EMG classification either require supervised ground-truth timestamps of the movement status or only contain limited kinematic variations. In this study, we propose a framework for classifying dynamic EMG signals into gestures and examine the impact of different movement phases, using an unsupervised method to segment and label the action transitions. We collected and utilized data from large gesture vocabularies with multiple dynamic actions to encode the transitions from one grasp intent to another based on natural sequences of human grasp movements. The classifier for identifying the gesture label was constructed afterward based on the dynamic EMG signal, with no supervised annotation of kinematic movements required. Finally, we evaluated the performances of several training strategies using EMG data from different movement phases and explored the information revealed from each phase. All experiments were evaluated in a real-time style with the performance transitions presented over time.

2. Generating unified platforms using multigranularity domain DSE (MG-DmDSE) exploiting application similarities

   Jinghan Zhang ,  Aly Sultan ,  Mehrshad Zandigohar , and 1 more author

   IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022

2021

1. MG-DmDSE: Multi-Granularity Domain Design Space Exploration Considering Function Similarity

   J. Zhang ,  A. Sultan ,  H. Tabkhi , and 1 more author

   In 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) , 2021
2. Classifications of Dynamic EMG in Hand Gesture and Unsupervised Grasp Motion Segmentation

   Han Han ,  Mehrshad Zandigohar ,  Mariusz P. Furmanek , and 3 more authors

   In Proceedings of the EMBS Annual International Conference , Nov 2021
3. NetCut: Real-Time DNN Inference Using Layer Removal

   Mehrshad Zandigohar ,  Deniz Erdogmus ,  and  Gunar Schirner

   In Design, Automation and Test in Europe Conference (DATE) , Feb 2021
4. RDP 3: Rapid Domain Platform Performance Prediction for Design Space Exploration

   Jinghan Zhang ,  Mehrshad Zandigohar ,  and  Gunar Schirner

   In 2021 IEEE 39th International Conference on Computer Design (ICCD) , Feb 2021

2020

1. Allocating One Common ACC-Rich Platform for Many Streaming Applications

   J. Zhang ,  H. Tabkhi ,  and  G. Schirner

   IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Feb 2020
2. HANDS: a multimodal dataset for modeling toward human grasp intent inference in prosthetic hands

   Mo Han ,  Sezen Yağmur Günay ,  Gunar Schirner , and 2 more authors

   Intelligent service robotics, Feb 2020
3. Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand

   Mehrshad Zandigohar ,  Mo Han ,  Deniz Erdoğmuş , and 1 more author

   Feb 2020

2019

1. Mitigating Application Diversity for Allocating a Unified ACC-Rich Platform

   J. Zhang ,  H. Tabkhi ,  and  G. Schirner

   In 2019 IEEE 37th International Conference on Computer Design (ICCD) , Feb 2019

2018

1. Alleviating Scalability Limitation of Accelerator-based Platforms

   N. Teimouri ,  H. Tabkhi ,  and  G. Schirner

   IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018
2. DS-DSE: Domain-Specific Design Space Exploration for Streaming Applications

   J. Zhang ,  H. Tabkhi ,  and  G. Schirner

   In Design, Automation & Test in Europe Conference & Exhibition (DATE) , 2018

2016

1. Framework for Rapid Development of Embedded Human-in-the-Loop Cyber-Physical Systems

   S. Feng ,  F. Quivira ,  and  G. Schirner

   In 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) , Oct 2016
2. Function-Level Processor (FLP): A Novel Processor Class for Efficient Processing of Streaming Applications

   H. Tabkhi ,  R. Bushey ,  and  G. Schirner

   Journal of Signal Processing Systems, Oct 2016
3. Improving scalability of CMPs with dense ACCs coverage

   N. Teimouri ,  H. Tabkhi ,  and  G. Schirner

   In Design, Automation & Test in Europe Conference & Exhibition (DATE) , Oct 2016

2015

1. Revisiting Accelerator-Based CMPs: Challenges and Solutions

   N. Teimouri ,  H. Tabkhi ,  and  G. Schirner

   Jun 2015

2014

1. Function-level processor (FLP): a high performance, minimal bandwidth, low power architecture for market-oriented MPSoCs

   H. Tabkhi ,  R. Bushey ,  and  G. Schirner

   IEEE Embedded Systems Letters, Jun 2014

2013

1. Joint Algorithm Developing and System-Level Design: Case Study on Video Encoding

   Jiaxing Zhang ,  and  Gunar Schirner

   In Embedded Systems: Design, Analysis and Verification , Jun 2013
2. The Future of Human-in-the-Loop Cyber-Physical Systems

   Gunar Schirner ,  Deniz Erdogmus ,  Kaushik Chowdhury , and 1 more author

   IEEE Computer, Jun 2013

   Abs

   Human-in-the-Loop Cyber-Physical-Systems (HiLCPS) is a challenging and very promising class of applications with immense potential of impacting daily lives of many people. HiLCPS systems measure cognitive activity through body and brain sensors, infer the intent through analysis on an embedded system, they then translate the intent into robot control signals influencing the physical environment by robotic actuators, where the effects are then again observed by the human as an input for new decisions – closing the loop. This article overviews HiLCPS opportunities and design challenges from the view of 4 disciplines: embedded system design, brain-computer interface algorithm design, assistive robotics, and innovative networking. The article outlines a common design scheme unifying these disciplines.

2012

1. A Mobile Platform Approach to integrating active learing accross the EE/CE/ICT Engineering Curriculum

   Mihir Ravel ,  Gunar Schirner ,  and  David Kaeli

   In Proceedings of the European Workshop on Microelectronics Education , May 2012

2009

1. Embedded System Design: Modeling, Synthesis and Verification

   Daniel D. Gajski ,  Samar Abdi ,  Andreas Gerstlauer , and 1 more author

   May 2009
2. High-Level Development, Modeling and Automatic Generation of Hardware-dependent Software

   Gunar Schirner ,  Rainer Dömer ,  and  Andreas Gerstlauer

   In Hardware Dependent Software: Principles and Practice , May 2009