Suhaidi Shafie

About

Suhaidi Shafie is a multidisciplinary researcher whose work spans robotics, biomedical engineering, and autonomous systems, with particular expertise in surface electromyography (sEMG)-controlled assistive devices and unmanned aerial vehicles. His most widely cited contribution, a comprehensive 2017 review of quadcopter UAVs (36 citations), established a foundational reference for researchers exploring civilian and military applications of multirotor systems. Alongside this, his 2019 review of sEMG-controlled hand robotic rehabilitation devices (33 citations) has become a key resource for those developing assistive technologies for stroke survivors and individuals with upper limb impairments. A central thread of Shafie's research is improving the reliability of sEMG-based control systems. He developed amplitude-independent muscle activity detection algorithms that overcome signal noise variability — a persistent obstacle to practical deployment of robotic prosthetics and orthoses — and demonstrated their application in soft robotic glove systems. His work identifying optimal forearm muscle sites for single-channel control reflects a commitment to simplifying these devices for real-world daily use. With additional contributions in MEMS force sensing and autonomous UAV gas monitoring, Shafie's research portfolio reflects a consistent drive to translate engineering innovation into practical, human-centered solutions.

Research Focus

Key Achievements

Top Papers

1. 1
   Unmanned Aerial Vehicle Quadcopter: A Review

   36 citations · 2017
2. 2
   A Review on Surface Electromyography-Controlled Hand Robotic Devices Used for Rehabilitation and Assistance in Activities of Daily Living

   33 citations · 2019
3. 3
   Soft robotic glove system controlled with amplitude independent muscle activity detection algorithm by using single sEMG channel

   9 citations · 2018
4. 4
   An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal

   9 citations · 2017
5. 5
   Identifying the Best Forearm Muscle to Control Soft Robotic Glove System by Using a Single sEMG Channel

   7 citations · 2020
6. 6
   Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors

   5 citations · 2020
7. 7
   Autonomous Quadcopter Altitude for Measuring Risky Gases in Hazard Area

   5 citations · 2018
8. 8
   Amplitude independent versus amplitude dependent muscle activity detection algorithms: a comparative study

   3 citations · 2020
9. 9
   An Experiment of Thick Film Force Sensor Using MEMS Simulation Software.

   3 citations · 2013

Key Collaborators

Contact & Links