Adriano A. G. Siqueira

About

Adriano A. G. Siqueira is a prominent robotics and biomedical engineering researcher whose work sits at the intersection of rehabilitation robotics, advanced control theory, and wearable sensing technologies. His research has made substantial contributions to the development of intelligent assistive and rehabilitative systems, with a particular focus on impedance control strategies for robotic therapy. Siqueira has pioneered adaptive impedance control frameworks applied to ankle and knee rehabilitation, including EMG-driven and model predictive control approaches, garnering hundreds of citations across these efforts. His fault-tolerant robot control work, employing Markovian jump models with H₂, H∞, and mixed H₂/H∞ strategies, has become a foundational reference in robust manipulator design (71 citations). Siqueira has also advanced wearable sensing instrumentation, developing polymer optical fiber sensors for gait analysis and real-time IMU-based gait event identification in impaired individuals—critical tools for patient-tailored robotic gait therapy. Beyond hardware and control, he has explored serious games integrated with rehabilitation robotics, applying reinforcement learning to dynamically match game difficulty to patient capability, promoting engagement and motor recovery. With a body of work exceeding 500 cumulative citations across his top papers, Siqueira has established himself as a leading figure in intelligent rehabilitation systems research.

Research Focus

Key Achievements

Top Papers

1. 1
   Polymer Optical Fiber Sensors in Wearable Devices: Toward Novel Instrumentation Approaches for Gait Assistance Devices

   72 citations · 2018
2. 2
   A Fault-Tolerant Manipulator Robot Based on ${{\cal H}}_2$, ${{\cal H}}_{\infty }$, and Mixed ${{\cal H}}_2/{{\cal H}}_{\infty }$ Markovian Controls

   71 citations · 2009
3. 3
   Adaptive Impedance Control Applied to Robot-Aided Neuro-Rehabilitation of the Ankle

   68 citations · 2018
4. 4
   Real-Time Identification of Gait Events in Impaired Subjects Using a Single-IMU Foot-Mounted Device

   61 citations · 2019
5. 5
   Feasibility of an optimal EMG-driven adaptive impedance control applied to an active knee orthosis

   51 citations · 2018
6. 6
   Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach

   49 citations · 2017
7. 7
   Optimal impedance via model predictive control for robot-aided rehabilitation

   46 citations · 2019
8. 8
   Assist-as-needed ankle rehabilitation based on adaptive impedance control

   40 citations · 2015
9. 9
   Dynamic Player Modelling in Serious Games Applied to Rehabilitation Robotics

   37 citations · 2014
10. 10
    Adaptive strategy for multi-user robotic rehabilitation games

    36 citations · 2011

Key Collaborators

Contact & Links