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  1. Abstract Background

    A robotic rehabilitation gym can be defined as multiple patients training with multiple robots or passive sensorized devices in a group setting. Recent work with such gyms has shown positive rehabilitation outcomes; furthermore, such gyms allow a single therapist to supervise more than one patient, increasing cost-effectiveness. To allow more effective multipatient supervision in future robotic rehabilitation gyms, we propose an automated system that could dynamically assign patients to different robots within a session in order to optimize rehabilitation outcome.


    As a first step toward implementing a practical patient-robot assignment system, we present a simplified mathematical model of a robotic rehabilitation gym. Mixed-integer nonlinear programming algorithms are used to find effective assignment and training solutions for multiple evaluation scenarios involving different numbers of patients and robots (5 patients and 5 robots, 6 patients and 5 robots, 5 patients and 7 robots), different training durations (7 or 12 time steps) and different complexity levels (whether different patients have different skill acquisition curves, whether robots have exit times associated with them). In all cases, the goal is to maximize total skill gain across all patients and skills within a session.


    Analyses of variance across different scenarios show that disjunctive and time-indexedmore »optimization models significantly outperform two baseline schedules: staying on one robot throughout a session and switching robots halfway through a session. The disjunctive model results in higher skill gain than the time-indexed model in the given scenarios, and the optimization duration increases as the number of patients, robots and time steps increases. Additionally, we discuss how different model simplifications (e.g., perfectly known and predictable patient skill level) could be addressed in the future and how such software may eventually be used in practice.


    Though it involves unrealistically simple scenarios, our study shows that intelligently moving patients between different rehabilitation robots can improve overall skill acquisition in a multi-patient multi-robot environment. While robotic rehabilitation gyms are not yet commonplace in clinical practice, prototypes of them already exist, and our study presents a way to use intelligent decision support to potentially enable more efficient delivery of technologically aided rehabilitation.

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  2. Free, publicly-accessible full text available September 1, 2023
  3. Free, publicly-accessible full text available July 25, 2023
  4. Free, publicly-accessible full text available August 1, 2023
  5. Carbon dioxide (CO 2 ) supersaturation in lakes and rivers worldwide is commonly attributed to terrestrial–aquatic transfers of organic and inorganic carbon (C) and subsequent, in situ aerobic respiration. Methane (CH 4 ) production and oxidation also contribute CO 2 to freshwaters, yet this remains largely unquantified. Flood pulse lakes and rivers in the tropics are hypothesized to receive large inputs of dissolved CO 2 and CH 4 from floodplains characterized by hypoxia and reducing conditions. We measured stable C isotopes of CO 2 and CH 4 , aerobic respiration, and CH 4 production and oxidation during two flood stages in Tonle Sap Lake (Cambodia) to determine whether dissolved CO 2 in this tropical flood pulse ecosystem has a methanogenic origin. Mean CO 2 supersaturation of 11,000 ± 9,000 μ atm could not be explained by aerobic respiration alone. 13 C depletion of dissolved CO 2 relative to other sources of organic and inorganic C, together with corresponding 13 C enrichment of CH 4 , suggested extensive CH 4 oxidation. A stable isotope-mixing model shows that the oxidation of 13 C depleted CH 4 to CO 2 contributes between 47 and 67% of dissolved CO 2 in Tonle Sap Lake.more »13 C depletion of dissolved CO 2 was correlated to independently measured rates of CH 4 production and oxidation within the water column and underlying lake sediments. However, mass balance indicates that most of this CH 4 production and oxidation occurs elsewhere, within inundated soils and other floodplain habitats. Seasonal inundation of floodplains is a common feature of tropical freshwaters, where high reported CO 2 supersaturation and atmospheric emissions may be explained in part by coupled CH 4 production and oxidation.« less
    Free, publicly-accessible full text available February 22, 2023
  6. Back injuries and other occupational injuries are common in workers who engage in long, arduous physical labor. The risk of these injuries could be reduced using assistive devices that automatically detect an object lifting motion and support the user while they perform the lift; however, such devices must be able to detect the lifting motion as it occurs. We thus developed a system to detect the start and end of a lift (performed as a stoop or squat) in real time based on pelvic angle and the distance between the user's hands and the user's center of mass. The measurements were input to an algorithm that first searches for hand-center distance peaks in a sliding window, then checks the pelvic displacement angle to verify lift occurrence. The approach was tested with 5 participants, who performed a total of 100 lifts of four different types. The times of actual lifts were determined by manual video annotation. The median time error (absolute difference between detected and actual occurrence time) for lifts that were not false negatives was 0.11 s; a lift was considered a false negative if it was not detected within two seconds of it actually occurring. Furthermore, 95% of liftsmore »that were detected occurred within 0.28 s of actual occurrence. This shows that it is possible to reliably detect lifts in real time based on the pelvic displacement angle and the distance between the user's hands and their center of mass.« less
  7. Free, publicly-accessible full text available January 1, 2023
  8. Trunk exoskeletons are wearable devices that support wearers during physically demanding tasks by reducing biomechanical loads and increasing stability. In this paper, we present a prototype sensorized passive trunk exoskeleton, which includes five motion processing units (3-axis accelerometers and gyroscopes with onboard digital processing), four one-axis flex sensors along the exoskeletal spinal column, and two one-axis force sensors for measuring the interaction force between the wearer and exoskeleton. A pilot evaluation of the exoskeleton was conducted with two wearers, who performed multiple everyday tasks (sitting on a chair and standing up, walking in a straight line, picking up a box with a straight back, picking up a box with a bent back, bending forward while standing, bending laterally while standing) while wearing the exoskeleton. Illustrative examples of the results are presented as graphs. Finally, potential applications of the sensorized exoskeleton as the basis for a semi-active exoskeleton design or for audio/haptic feedback to guide the wearer are discussed.
  9. Investigating the earliest stages of crystallization requires the transmission electron microscope (TEM) and is particularly challenging for materials which can be affected by the electron beam. Typically, when imaging at magnifications high enough to observe local crystallinity, the electron beam's current density must be high to produce adequate image contrast. Yet, minimizing the electron dose is necessary to reduce the changes caused by the beam. With the advent of a sensitive, high-speed, direct-detection camera for a TEM that is corrected for spherical aberration, it is possible to probe the early stages of crystallization at the atomic scale. High-quality images with low contrast can now be analyzed using new computing methods. In the present paper, this approach is illustrated for crystallization in a Ge 2 Sb 2 Te 5 (GST-225) phase-change material which can undergo particularly rapid phase transformations and is sensitive to the electron beam. A thin (20 nm) film of GST-225 has been directly imaged in the TEM and the low-dose images processed using Python scripting to extract details of the nanoscale nuclei. Quantitative analysis of the processed images in a video sequence also allows the growth of such nuclei to be followed.