Robust Generalized Proportional Integral Control for Trajectory Tracking of Soft Actuators in a Pediatric Wearable Assistive Device

Mucchiani, Caio; Liu, Zhichao; Sahin, Ipsita; Kokkoni, Elena; Karydis, Konstantinos

doi:10.1109/iros55552.2023.10342528

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Cited by 2 publications

References 33 publications

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A Fabric-based Pneumatic Actuator for the Infant Elbow: Design and Comparative Kinematic Analysis

Sahin,

Ayazi,

Mucchiani

et al. 2023

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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A Fabric-based Pneumatic Actuator for the Infant Elbow: Design and Comparative Kinematic Analysis

Sahin,

Ayazi,

Mucchiani

et al. 2023

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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E-BabyNet: Enhanced Action Recognition of Infant Reaching in Unconstrained Environments

Dechemi,

Karydis

2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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Machine vision and artificial intelligence hold promise across healthcare applications. In this paper, we focus on the emerging research direction of infant action recognition, and we specifically consider the task of reaching which is an important developmental milestone. We develop E-babyNet, a lightweight yet effective neuralnetwork-based framework for infant action recognition that leverages the spatial and temporal correlation of bounding boxes of infants' hands and objects to reach for to determine the onset and offset of the reaching action. E-babyNet consists of two main layers based on two LSTM and a Bidirectional LSTM (BiLSTM) model, respectively. The first layer provides a pre-evaluation of the reaching action for each hand by providing onset and offset keyframes.Then, the biLSTM model merges the previous outputs to deliver an outcome of the reaching actions detection for each frame including the reaching hand. We evaluated our approach against four other lightweight structures using a dataset comprising 5,865 annotated images resulting in 16,337 bounding boxes from 375 distinctive infant reaching actions performed while sitting by different subjects in unconstrained (home/clinic) environments. Results illustrate the effectiveness of our approach and ability to provide reliable reaching action detection and offer onset and offset keyframes with a precision of one frame. Moreover, the biLSTM layer can handle the transition between reaching actions and help reduce false detections.

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Robust Generalized Proportional Integral Control for Trajectory Tracking of Soft Actuators in a Pediatric Wearable Assistive Device

Cited by 2 publications

References 33 publications

A Fabric-based Pneumatic Actuator for the Infant Elbow: Design and Comparative Kinematic Analysis

A Fabric-based Pneumatic Actuator for the Infant Elbow: Design and Comparative Kinematic Analysis

E-BabyNet: Enhanced Action Recognition of Infant Reaching in Unconstrained Environments

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