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1. Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

   https://doi.org/10.1002/adrr.202500027  

   Wang, Yuxiao; Jiang, Zhipeng; Kwon, Sun Hwa; Ibrahim, Matthew; Dang, Alexander; Dong, Lin (July 2025, Advanced Robotics Research)

   Medical robotics has revolutionized healthcare by enhancing precision, adaptability, and clinical outcomes. This field has further evolved with the advent of human–machine interfaces (HMIs), which facilitate seamless interactions between users and robotic systems. However, traditional HMIs rely on rigid sensing components and bulky wiring, causing mechanical mismatches that limit user comfort, accuracy, and wearability. Flexible sensors offer a transformative solution by enabling the integration of adaptable sensing technology into HMIs, enhancing overall system functionality. Further integrating artificial intelligence (AI) into these systems addresses key limitations of conventional HMI, including challenges in complex data interpretations and multimodal sensing integration. In this review, we systematically explore the convergence of flexible sensor‐based HMIs and AI for medical robotics. Specifically, we analyze core flexible sensing mechanisms, AI‐driven advancements in healthcare, and applications in prosthetics, exoskeletons, and surgical robotics. By bridging the gap between flexible sensing technologies and AI‐driven intelligence, this review presents a roadmap for developing next‐generation smart medical robotic systems, advancing personalized healthcare and adaptive human–robot interactions. 

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2. "Compliant Magnetic FMG Array Dataset"

   https://doi.org/10.21227/j17n-c183  

   Cheng, Wen-Yu; Engeberg, Erik (January 2025, IEEE DataPort)

   {"Abstract":[""Control of powered prosthetic hands could benefit from improved techniques to infer the amputees\\u2019 desired grasp intentions. Force myography (FMG) has recently emerged as a potential alternative to electromyography, which is traditionally used in clinical practice.  Due to their practical and robust attributes, we introduce innovative compliant magnetic FMG sensor arrays for forearm muscle pattern recognition. Sensor arrays with 18 or 24 compliant magnetic FMG sensor modules were created, demonstrating the customizability of our Scan2Make process for creating individualized sockets with integrated FMG sensor arrays for varying limb differences. Real-time control experiments with subject-specific artificial neural networks (ANN) showed that non-amputees were able to produce 15.43 \\u00b1 2.37 grasp gesture classes with over 90% accuracy. The three amputees produced an average of 9.00 \\u00b1 3.61 gestures with over 90% accuracy in real-time. Additionally, principal component analysis (PCA) was used to both reduce sensor count and improve classification accuracy in subsequent real-time playback analyses. Seven out of ten subjects achieved their highest accuracy with a reduced number of compliant magnetic sensor modules. To our best knowledge, this study is the first to use arrays of compliant magnetic sensors for forearm muscle pattern recognition to enable real-time control of a robotic hand. Furthermore, this is the first effort to use a 3D scanning and printing approach to create custom prosthetic sockets with any kind of integrated FMG sensor. Additionally, we are providing the first open-source database of FMG signals from 3 amputees and 7 non-amputees using the compliant magnetic sensor arrays as a resource for the research community. These novel compliant magnetic FMG sensor arrays have the potential to advance the state of the art for prosthetic hand control and could be used broadly in the fields of tactile sensing, haptics, teleoperation, and rehabilitation. ""]} 

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3. Understanding the capacity of children with congenital unilateral below-elbow deficiency to actuate their affected muscles

   https://doi.org/10.1038/s41598-024-54952-7  

   Battraw, Marcus A; Fitzgerald, Justin; James, Michelle A; Bagley, Anita M; Joiner, Wilsaan M; Schofield, Jonathon S (December 2024, Scientific Reports)

   Abstract In recent years, commercially available dexterous upper limb prostheses for children have begun to emerge. These devices derive control signals from surface electromyography (measure of affected muscle electrical activity, sEMG) to drive a variety of grasping motions. However, the ability for children with congenital upper limb deficiency to actuate their affected muscles to achieve naturalistic prosthetic control is not well understood, as compared to adults or children with acquired hand loss. To address this gap, we collected sEMG data from 9 congenital one-handed participants ages 8–20 years as they envisioned and attempted to perform 10 different movements with their missing hands. Seven sEMG electrodes were adhered circumferentially around the participant’s affected and unaffected limbs and participants mirrored the attempted missing hand motions with their intact side. To analyze the collected sEMG data, we used time and frequency domain analyses. We found that for the majority of participants, attempted hand movements produced detectable and consistent muscle activity, and the capacity to achieve this was not dissimilar across the affected and unaffected sides. These data suggest that children with congenital hand absence retain a degree of control over their affected muscles, which has important implications for translating and refining advanced prosthetic control technologies for children. 

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4. Moving a missing hand: children born with below elbow deficiency can enact hand grasp patterns with their residual muscles

   https://doi.org/10.1186/s12984-024-01306-z  

   Fitzgerald, Justin J; Battraw, Marcus A; James, Michelle A; Bagley, Anita M; Schofield, Jonathon S; Joiner, Wilsaan M (January 2024, Journal of NeuroEngineering and Rehabilitation)

   Abstract Children with a unilateral congenital below elbow deficiency (UCBED) have one typical upper limb and one that lacks a hand, ending below the elbow at the proximal/mid forearm. UCBED is an isolated condition, and affected children otherwise develop normal sensorimotor control. Unlike adults with upper limb absence, the majority of whom have an acquired loss, children with UCBED never developed a hand, so their residual muscles have never actuated an intact limb. Their ability to purposefully modulate affected muscle activity is often assumed to be limited, and this assumption has influenced prosthetic design and prescription practices for this population as many modern devices derive control signals from affected muscle activity. To better understand the motor capabilities of the affected muscles, we used ultrasound imaging to study 6 children with UCBED. We examined the extent to which subjects activate their affected muscles when performing mirrored movements with their typical and missing hands. We demonstrate that all subjects could intentionally and consistently enact at least five distinct muscle patterns when attempting different missing hand movements (e.g., power grasp) and found similar performance across affected and typically developed limbs. These results suggest that although participants had never actuated the missing hand they could distinctively and consistently activate the residual muscle patterns associated with actions on the unaffected side. These findings indicate that motor control still develops in the absence of the normal effector, and can serve as a guide for developing prostheses that leverage the full extent of these children’s motor control capabilities. 

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5. Exploring Holistic HMI Design for Automated Vehicles: Insights from a Participatory Workshop to Bridge In-Vehicle and External Communication

   https://doi.org/10.1145/3613905.3651086  

   Dong, Haoyu; Tran, Tram_Thi Minh; Verstegen, Rutger; Cazacu, Silvia; Gao, Ruolin; Hoggenmüller, Marius; Dey, Debargha; Franssen, Mervyn; Sasalovici, Markus; Bazilinskyy, Pavlo; et al (May 2024, ACM)

   Human–Machine Interfaces (HMIs) for automated vehicles (AVs) are typically divided into two categories: internal HMIs for inter- actions within the vehicle, and external HMIs for communication with other road users. In this work, we examine the prospects of bridging these two seemingly distinct domains. Through a partici- patory workshop with automotive user interface researchers and practitioners, we facilitated a critical exploration of holistic HMI design by having workshop participants collaboratively develop interaction scenarios involving AVs, in-vehicle users, and external road users. The discussion o!ers insights into the escalation of interface elements as an HMI design strategy, the direct interac- tions between di!erent users, and an expanded understanding of holistic HMI design. This work re"ects a collaborative e!ort to understand the practical aspects of this holistic design approach, o!ering new perspectives and encouraging further investigation into this underexplored aspect of automotive user interfaces. 

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