Ravi Vaidyanathan | Case Western Reserve University (original) (raw)
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Papers by Ravi Vaidyanathan
IEEE Robotics and Automation Letters
Parkinson's disease (PD) is a neurodegenerative condition that affects the normal motor funct... more Parkinson's disease (PD) is a neurodegenerative condition that affects the normal motor function of the brain. Automated sensor systems are unique sensor modalities that have been combined together for a specific function. In this thesis, an automated sensor system that tracks and records PD motor symptoms in a clinical setting is proposed. The motor symptoms that were targeted for quantification were rigidity, bradykinesia and tremor. The automated sensor system produced here is called the Parkinson's diagnostic device (PDD) and comprised of a force sensor, motion sensors and muscle activity sensors to measure PD motor symptoms. All accompanying software interfacing libraries and graphical user interfaces developed were described in this thesis as well. The Unified Parkinson's disease Rating Scale (UPDRS) is currently the gold standard used by clinicians to measure and rate the severity of motor symptoms. As such, during subject testing, the UPDRS score given by the cli...
Design modifications have improved the durability and performance of a previously developed hybri... more Design modifications have improved the durability and performance of a previously developed hybrid vehicle capable of both aerial and terrestrial locomotion. Whereas the original vehicle could fly, land, and crawl in sequence, it suffered from limited durability, as evidenced by catastrophic failure after a small number of landings – two to four depending on the substrate. The two most common failure modes were breakage of the terrestrial locomotion drive servos and separation of components from the fuselage. Evaluation of the original vehicle also identified the need for an autopilot. This further complicated the durability problem by greatly increasing the vehicle’s mass, causing larger impulses in high speed landings. The new fuselage design includes a well-defined nacelle to which the propeller motor is securely mounted. All metal DC motors replace R/C servos in the terrestrial drive system, and a slip clutch limits the torque experienced by the motor during landing. The slip cl...
IEEE Transactions on Medical Robotics and Bionics, 2021
IEEE Transactions on Biomedical Engineering, 2020
IEEE ... International Conference on Rehabilitation Robotics : [proceedings], Jul 1, 2017
The mechanical advantages of bio-inspired condylar robotic knee joints for use in prosthetics or ... more The mechanical advantages of bio-inspired condylar robotic knee joints for use in prosthetics or rehabilitation has been argued extensively in literature. A common limitation of these designs is the difficulty of estimating joint angle and therefore accurately controlling the joint. Furthermore, the potential role of ligament-like structures in robotic knees is not very well established. In this work, we investigate the role of compliant stretch sensing ligaments and their integration into a condylar robotic knee. Simulations and experiments are executed out in order to establish whether measurement of stretch in these structures can be used to produce a new feedback controller for joint position. We report results from a computer model, as well as the design and construction of a robotic knee that show, for a chosen condyle shape, ligament stretch is a function of muscle force and joint velocity as well as joint angle. We have developed a genetic algorithm optimised controller inco...
2015 IEEE International Conference on Automation Science and Engineering (CASE), 2015
WIT Transactions on The Built Environment, 2009
Sensors, 2021
We introduce a set of input models for fusing information from ensembles of wearable sensors supp... more We introduce a set of input models for fusing information from ensembles of wearable sensors supporting human performance and telemedicine. Veracity is demonstrated in action classification related to sport, specifically strikes in boxing and taekwondo. Four input models, formulated to be compatible with a broad range of classifiers, are introduced and two diverse classifiers, dynamic time warping (DTW) and convolutional neural networks (CNNs) are implemented in conjunction with the input models. Seven classification models fusing information at the input-level, output-level, and a combination of both are formulated. Action classification for 18 boxing punches and 24 taekwondo kicks demonstrate our fusion classifiers outperform the best DTW and CNN uni-axial classifiers. Furthermore, although DTW is ostensibly an ideal choice for human movements experiencing non-linear variations, our results demonstrate deep learning fusion classifiers outperform DTW. This is a novel finding given ...
2015 IEEE International Conference on Automation Science and Engineering (CASE), 2015
Proceedings of the 1st …, 2007
This paper describes the experimental design, implementation, and testing of a network for tele-c... more This paper describes the experimental design, implementation, and testing of a network for tele-command, control, and communications of micro robots over long distances. The system utilizes commercial low bandwidth satellites to transmit near real-time video ...
Sensors
Neurorobotic augmentation (e.g., robotic assist) is now in regular use to support individuals suf... more Neurorobotic augmentation (e.g., robotic assist) is now in regular use to support individuals suffering from impaired motor functions. A major unresolved challenge, however, is the excessive cognitive load necessary for the human–machine interface (HMI). Grasp control remains one of the most challenging HMI tasks, demanding simultaneous, agile, and precise control of multiple degrees-of-freedom (DoFs) while following a specific timing pattern in the joint and human–robot task spaces. Most commercially available systems use either an indirect mode-switching configuration or a limited sequential control strategy, limiting activation to one DoF at a time. To address this challenge, we introduce a shared autonomy framework centred around a low-cost multi-modal sensor suite fusing: (a) mechanomyography (MMG) to estimate the intended muscle activation, (b) camera-based visual information for integrated autonomous object recognition, and (c) inertial measurement to enhance intention predic...
IEEE Transactions on Cognitive and Developmental Systems
IEEE Internet of Things Journal
Frontiers in Robotics and AI
COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adul... more COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adults, who face unprecedented isolation. Consequences, while globally severe, are acutely pronounced in low- and middle-income countries (LMICs) confronting pronounced gaps in resources and clinician accessibility. Social robots are well-recognized for their potential to support mental health, yet user compliance (i.e., trust) demands seamless affective human-robot interactions; natural ‘human-like’ conversations are required in simple, inexpensive, deployable platforms. We present the design, development, and pilot testing of a multimodal robotic framework fusing verbal (contextual speech) and nonverbal (facial expressions) social cues, aimed to improve engagement in human-robot interaction and ultimately facilitate mental health telemedicine during and beyond the COVID-19 pandemic. We report the design optimization of a hybrid face robot, which combines digital facial expressions based on...
Sensors
Fetal movements (FM) are an important factor in the assessment of fetal health. However, there is... more Fetal movements (FM) are an important factor in the assessment of fetal health. However, there is currently no reliable way to monitor FM outside clinical environs. While extensive research has been carried out using accelerometer-based systems to monitor FM, the desired accuracy of detection is yet to be achieved. A major challenge has been the difficulty of testing and calibrating sensors at the pre-clinical stage. Little is known about fetal movement features, and clinical trials involving pregnant women can be expensive and ethically stringent. To address these issues, we introduce a novel FM simulator, which can be used to test responses of sensor arrays in a laboratory environment. The design uses a silicon-based membrane with material properties similar to that of a gravid abdomen to mimic the vibrations due to fetal kicks. The simulator incorporates mechanisms to pre-stretch the membrane and to produce kicks similar to that of a fetus. As a case study, we present results fro...
IEEE Transactions on Neural Systems and Rehabilitation Engineering
IEEE Transactions on Neural Systems and Rehabilitation Engineering
IEEE/ASME Transactions on Mechatronics
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology
IEEE Robotics and Automation Letters
Parkinson's disease (PD) is a neurodegenerative condition that affects the normal motor funct... more Parkinson's disease (PD) is a neurodegenerative condition that affects the normal motor function of the brain. Automated sensor systems are unique sensor modalities that have been combined together for a specific function. In this thesis, an automated sensor system that tracks and records PD motor symptoms in a clinical setting is proposed. The motor symptoms that were targeted for quantification were rigidity, bradykinesia and tremor. The automated sensor system produced here is called the Parkinson's diagnostic device (PDD) and comprised of a force sensor, motion sensors and muscle activity sensors to measure PD motor symptoms. All accompanying software interfacing libraries and graphical user interfaces developed were described in this thesis as well. The Unified Parkinson's disease Rating Scale (UPDRS) is currently the gold standard used by clinicians to measure and rate the severity of motor symptoms. As such, during subject testing, the UPDRS score given by the cli...
Design modifications have improved the durability and performance of a previously developed hybri... more Design modifications have improved the durability and performance of a previously developed hybrid vehicle capable of both aerial and terrestrial locomotion. Whereas the original vehicle could fly, land, and crawl in sequence, it suffered from limited durability, as evidenced by catastrophic failure after a small number of landings – two to four depending on the substrate. The two most common failure modes were breakage of the terrestrial locomotion drive servos and separation of components from the fuselage. Evaluation of the original vehicle also identified the need for an autopilot. This further complicated the durability problem by greatly increasing the vehicle’s mass, causing larger impulses in high speed landings. The new fuselage design includes a well-defined nacelle to which the propeller motor is securely mounted. All metal DC motors replace R/C servos in the terrestrial drive system, and a slip clutch limits the torque experienced by the motor during landing. The slip cl...
IEEE Transactions on Medical Robotics and Bionics, 2021
IEEE Transactions on Biomedical Engineering, 2020
IEEE ... International Conference on Rehabilitation Robotics : [proceedings], Jul 1, 2017
The mechanical advantages of bio-inspired condylar robotic knee joints for use in prosthetics or ... more The mechanical advantages of bio-inspired condylar robotic knee joints for use in prosthetics or rehabilitation has been argued extensively in literature. A common limitation of these designs is the difficulty of estimating joint angle and therefore accurately controlling the joint. Furthermore, the potential role of ligament-like structures in robotic knees is not very well established. In this work, we investigate the role of compliant stretch sensing ligaments and their integration into a condylar robotic knee. Simulations and experiments are executed out in order to establish whether measurement of stretch in these structures can be used to produce a new feedback controller for joint position. We report results from a computer model, as well as the design and construction of a robotic knee that show, for a chosen condyle shape, ligament stretch is a function of muscle force and joint velocity as well as joint angle. We have developed a genetic algorithm optimised controller inco...
2015 IEEE International Conference on Automation Science and Engineering (CASE), 2015
WIT Transactions on The Built Environment, 2009
Sensors, 2021
We introduce a set of input models for fusing information from ensembles of wearable sensors supp... more We introduce a set of input models for fusing information from ensembles of wearable sensors supporting human performance and telemedicine. Veracity is demonstrated in action classification related to sport, specifically strikes in boxing and taekwondo. Four input models, formulated to be compatible with a broad range of classifiers, are introduced and two diverse classifiers, dynamic time warping (DTW) and convolutional neural networks (CNNs) are implemented in conjunction with the input models. Seven classification models fusing information at the input-level, output-level, and a combination of both are formulated. Action classification for 18 boxing punches and 24 taekwondo kicks demonstrate our fusion classifiers outperform the best DTW and CNN uni-axial classifiers. Furthermore, although DTW is ostensibly an ideal choice for human movements experiencing non-linear variations, our results demonstrate deep learning fusion classifiers outperform DTW. This is a novel finding given ...
2015 IEEE International Conference on Automation Science and Engineering (CASE), 2015
Proceedings of the 1st …, 2007
This paper describes the experimental design, implementation, and testing of a network for tele-c... more This paper describes the experimental design, implementation, and testing of a network for tele-command, control, and communications of micro robots over long distances. The system utilizes commercial low bandwidth satellites to transmit near real-time video ...
Sensors
Neurorobotic augmentation (e.g., robotic assist) is now in regular use to support individuals suf... more Neurorobotic augmentation (e.g., robotic assist) is now in regular use to support individuals suffering from impaired motor functions. A major unresolved challenge, however, is the excessive cognitive load necessary for the human–machine interface (HMI). Grasp control remains one of the most challenging HMI tasks, demanding simultaneous, agile, and precise control of multiple degrees-of-freedom (DoFs) while following a specific timing pattern in the joint and human–robot task spaces. Most commercially available systems use either an indirect mode-switching configuration or a limited sequential control strategy, limiting activation to one DoF at a time. To address this challenge, we introduce a shared autonomy framework centred around a low-cost multi-modal sensor suite fusing: (a) mechanomyography (MMG) to estimate the intended muscle activation, (b) camera-based visual information for integrated autonomous object recognition, and (c) inertial measurement to enhance intention predic...
IEEE Transactions on Cognitive and Developmental Systems
IEEE Internet of Things Journal
Frontiers in Robotics and AI
COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adul... more COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adults, who face unprecedented isolation. Consequences, while globally severe, are acutely pronounced in low- and middle-income countries (LMICs) confronting pronounced gaps in resources and clinician accessibility. Social robots are well-recognized for their potential to support mental health, yet user compliance (i.e., trust) demands seamless affective human-robot interactions; natural ‘human-like’ conversations are required in simple, inexpensive, deployable platforms. We present the design, development, and pilot testing of a multimodal robotic framework fusing verbal (contextual speech) and nonverbal (facial expressions) social cues, aimed to improve engagement in human-robot interaction and ultimately facilitate mental health telemedicine during and beyond the COVID-19 pandemic. We report the design optimization of a hybrid face robot, which combines digital facial expressions based on...
Sensors
Fetal movements (FM) are an important factor in the assessment of fetal health. However, there is... more Fetal movements (FM) are an important factor in the assessment of fetal health. However, there is currently no reliable way to monitor FM outside clinical environs. While extensive research has been carried out using accelerometer-based systems to monitor FM, the desired accuracy of detection is yet to be achieved. A major challenge has been the difficulty of testing and calibrating sensors at the pre-clinical stage. Little is known about fetal movement features, and clinical trials involving pregnant women can be expensive and ethically stringent. To address these issues, we introduce a novel FM simulator, which can be used to test responses of sensor arrays in a laboratory environment. The design uses a silicon-based membrane with material properties similar to that of a gravid abdomen to mimic the vibrations due to fetal kicks. The simulator incorporates mechanisms to pre-stretch the membrane and to produce kicks similar to that of a fetus. As a case study, we present results fro...
IEEE Transactions on Neural Systems and Rehabilitation Engineering
IEEE Transactions on Neural Systems and Rehabilitation Engineering
IEEE/ASME Transactions on Mechatronics
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology