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1. Inclusion of actuator dynamics in simulations of assisted human movement

   https://doi.org/10.1002/cnm.3334  

   Nguyen, Vinh Q. ; LaPre, Andrew K. ; Price, Mark A. ; Umberger, Brian R. ; Sup, IV, Frank C. ( March 2020 , International Journal for Numerical Methods in Biomedical Engineering)

   Simulation of musculoskeletal systems using dynamic optimization is a powerful approach for studying the biomechanics of human movements and can be applied to human‐robot interactions. The simulation results of human movements augmented by robotic devices may be used to evaluate and optimize the device design and controller. However, simulations are limited by the accuracy of the models which are usually simplified for computation efficiency. Typically, the powered robotic devices are often modeled as massless, ideal torque actuators that is without mass and internal dynamics, which may have significant impacts on the simulation results. This article investigates the effects of including the mass and internal dynamics of the device in simulations of assisted human movement. The device actuator was modeled in various ways with different detail levels. Dynamic optimization was used to find the muscle activations and actuator commands in motion tracking and predictive simulations. The results showed that while the effects of device mass and inertia can be small, the electrical dynamics of the motor can significantly impact the results. This outcome suggests the importance of using an accurate actuator model in simulations of human movement augmented by assistive devices.

   Demonstrating the effects of including mass and internal dynamics of the actuator in simulations of assisted human movement

   A new OpenSim electric motor actuator class to capture the electromechanical dynamics for use in simulation of human movement assisted by powered robotic devices

    

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2. Reduction of Residual Vibration in Displacement-Amplified Micro-Electromagnetic Actuators with Non-linear Dynamics Using Input Shaping

   https://doi.org/10.1109/AIM.2018.8452238  

   Eaglin, Gerald ; Vaughan, Joshua ; Nabae, Hiroyuki ( July 2018 , 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM))

   Micro-electromagnetic actuators have been used in many fields and industries for systems such as microftuidic systems, positioning stages, and robotic manipulators. Small-scale electromagnetic actuators are able to provide rapid motion with high positioning accuracy. The actuator presented in this paper utilizes a displacement amplification mechanism to increase the maximum stroke length that can be achieved. The dynamics of this actuator are nonlinear due to the dependence of the applied force on gap distance between the coils and the amplification mechanism. This nonlinearity causes the performance of PID control to vary with respect to the displacement of the actuator. The control method proposed in this paper to limit the overshoot resulting from nonlinearity uses a combination of PID control and robust input shapers. Using robust input shapers to account for parameter variation across the workspace, the combined controller eliminates the overshoot while maintaining short settling times. Simulations are presented to demonstrate the performance of the proposed method. 

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3. American Sign Language Recognition Using RF Sensing

   https://doi.org/10.1109/JSEN.2020.3022376  

   Gurbuz, Sevgi Z. ; Gurbuz, Ali C. ; Malaia, Evie A. ; Griffin, Darrin J. ; Crawford, Chris ; Rahman, M. Mahbubur ; Kurtoglu, Emre ; Aksu, Ridvan ; Macks, Trevor ; Mdrafi, Robiulhossain ( September 2020 , IEEE Sensors Journal)

   Many technologies for human-computer interaction have been designed for hearing individuals and depend upon vocalized speech, precluding users of American Sign Language (ASL) in the Deaf community from benefiting from these advancements. While great strides have been made in ASL recognition with video or wearable gloves, the use of video in homes has raised privacy concerns, while wearable gloves severely restrict movement and infringe on daily life. Methods: This paper proposes the use of RF sensors for HCI applications serving the Deaf community. A multi-frequency RF sensor network is used to acquire non-invasive, non-contact measurements of ASL signing irrespective of lighting conditions. The unique patterns of motion present in the RF data due to the micro-Doppler effect are revealed using time-frequency analysis with the Short-Time Fourier Transform. Linguistic properties of RF ASL data are investigated using machine learning (ML). Results: The information content, measured by fractal complexity, of ASL signing is shown to be greater than that of other upper body activities encountered in daily living. This can be used to differentiate daily activities from signing, while features from RF data show that imitation signing by non-signers is 99% differentiable from native ASL signing. Feature-level fusion of RF sensor network data is used to achieve 72.5% accuracy in classification of 20 native ASL signs. Implications: RF sensing can be used to study dynamic linguistic properties of ASL and design Deaf-centric smart environments for non-invasive, remote recognition of ASL. ML algorithms should be benchmarked on native, not imitation, ASL data. 

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4. Quantification of Contractile Dynamic Complexities Exhibited by Human Stem Cell-Derived Cardiomyocytes Using Nonlinear Dimensional Analysis

   https://doi.org/10.1038/s41598-019-51197-7  

   Hoang, Plansky ; Jacquir, Sabir ; Lemus, Stephanie ; Ma, Zhen ( October 2019 , Scientific Reports)

   Understanding the complexity of biological signals has been gaining widespread attention due to increasing knowledge on the nonlinearity that exists in these systems. Cardiac signals are known to exhibit highly complex dynamics, consisting of high degrees of interdependency that regulate the cardiac contractile functions. These regulatory mechanisms are important to understand for the development of novelin vitrocardiac systems, especially with the exponential growth in deriving cardiac tissue directly from human induced pluripotent stem cells (hiPSCs). This work describes a unique analytical approach that integrates linear amplitude and frequency analysis of physical cardiac contraction, with nonlinear analysis of the contraction signals to measure the signals’ complexity. We generated contraction motion waveforms reflecting the physical contraction of hiPSC-derived cardiomyocytes (hiPSC-CMs) and implemented these signals to nonlinear analysis to compute the capacity and correlation dimensions. These parameters allowed us to characterize the dynamics of the cardiac signals when reconstructed into a phase space and provided a measure of signal complexity to supplement contractile physiology data. Thus, we applied this approach to evaluate drug response and observed that relationships between contractile physiology and dynamic complexity were unique to each tested drug. This illustrated the applicability of this approach in not only characterization of cardiac signals, but also monitoring and diagnostics of cardiac health in response to external stress.

    

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5. Co‐designing teacher support technology for problem‐based learning in middle school science

   https://doi.org/10.1111/bjet.13363  

   Hutchins, Nicole M. ; Biswas, Gautam ( July 2023 , British Journal of Educational Technology)

   This paper provides an experience report on a co‐design approach with teachers to co‐create learning analytics‐based technology to support problem‐based learning in middle school science classrooms. We have mapped out a workflow for such applications and developed design narratives to investigate the implementation, modifications and temporal roles of the participants in the design process. Our results provide precedent knowledge on co‐designing with experienced and novice teachers and co‐constructing actionable insight that can help teachers engage more effectively with their students' learning and problem‐solving processes during classroom PBL implementations.

   What is already known about this topic

   Success of educational technology depends in large part on the technology's alignment with teachers' goals for their students, teaching strategies and classroom context.

   Teacher and researcher co‐design of educational technology and supporting curricula has proven to be an effective way for integrating teacher insight and supporting their implementation needs.

   Co‐designing learning analytics and support technologies with teachers is difficult due to differences in design and development goals, workplace norms, and AI‐literacy and learning analytics background of teachers.

   What this paper adds

   We provide a co‐design workflow for middle school teachers that centres on co‐designing and developing actionable insights to support problem‐based learning (PBL) by systematic development of responsive teaching practices using AI‐generated learning analytics.

   We adapt established human‐computer interaction (HCI) methods to tackle the complex task of classroom PBL implementation, working with experienced and novice teachers to create a learning analytics dashboard for a PBL curriculum.

   We demonstrate researcher and teacher roles and needs in ensuring co‐design collaboration and the co‐construction of actionable insight to support middle school PBL.

   Implications for practice and/or policy

   Learning analytics researchers will be able to use the workflow as a tool to support their PBL co‐design processes.

   Learning analytics researchers will be able to apply adapted HCI methods for effective co‐design processes.

   Co‐design teams will be able to pre‐emptively prepare for the difficulties and needs of teachers when integrating middle school teacher feedback during the co‐design process in support of PBL technologies.

    

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