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1. Load Position and Weight Classification during Carrying Gait Using Wearable Inertial and Electromyographic Sensors

   https://doi.org/10.3390/s20174963  

   Goršič, Maja; Dai, Boyi; Novak, Domen (September 2020, Sensors)

   null (Ed.)

   Lifting and carrying heavy objects is a major aspect of physically intensive jobs. Wearable sensors have previously been used to classify different ways of picking up an object, but have seen only limited use for automatic classification of load position and weight while a person is walking and carrying an object. In this proof-of-concept study, we thus used wearable inertial and electromyographic sensors for offline classification of different load positions (frontal vs. unilateral vs. bilateral side loads) and weights during gait. Ten participants performed 19 different carrying trials each while wearing the sensors, and data from these trials were used to train and evaluate classification algorithms based on supervised machine learning. The algorithms differentiated between frontal and other loads (side/none) with an accuracy of 100%, between frontal vs. unilateral side load vs. bilateral side load with an accuracy of 96.1%, and between different load asymmetry levels with accuracies of 75–79%. While the study is limited by a lack of electromyographic sensors on the arms and a limited number of load positions/weights, it shows that wearable sensors can differentiate between different load positions and weights during gait with high accuracy. In the future, such approaches could be used to control assistive devices or for long-term worker monitoring in physically demanding occupations. 

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2. Treadmill vs. overground walking: different response to physical interaction

   https://doi.org/10.1152/jn.00176.2017  

   Ochoa, Julieth; Sternad, Dagmar; Hogan, Neville (October 2017, Journal of Neurophysiology)

   Rehabilitation of human motor function is an issue of growing significance, and human-interactive robots offer promising potential to meet the need. For the lower extremity, however, robot-aided therapy has proven challenging. To inform effective approaches to robotic gait therapy, it is important to better understand unimpaired locomotor control: its sensitivity to different mechanical contexts and its response to perturbations. The present study evaluated the behavior of 14 healthy subjects who walked on a motorized treadmill and overground while wearing an exoskeletal ankle robot. Their response to a periodic series of ankle plantar flexion torque pulses, delivered at periods different from, but sufficiently close to, their preferred stride cadence, was assessed to determine whether gait entrainment occurred, how it differed across conditions, and if the adapted motor behavior persisted after perturbation. Certain aspects of locomotor control were exquisitely sensitive to walking context, while others were not. Gaits entrained more often and more rapidly during overground walking, yet, in all cases, entrained gaits synchronized the torque pulses with ankle push-off, where they provided assistance with propulsion. Furthermore, subjects entrained to perturbation periods that required an adaption toward slower cadence, even though the pulses acted to accelerate gait, indicating a neural adaptation of locomotor control. Lastly, during 15 post-perturbation strides, the entrained gait period was observed to persist more frequently during overground walking. This persistence was correlated with the number of strides walked at the entrained gait period (i.e., longer exposure), which also indicated a neural adaptation. NEW & NOTEWORTHY We show that the response of human locomotion to physical interaction differs between treadmill and overground walking. Subjects entrained to a periodic series of ankle plantar flexion torque pulses that shifted their gait cadence, synchronizing ankle push-off with the pulses (so that they assisted propulsion) even when gait cadence slowed. Entrainment was faster overground and, on removal of torque pulses, the entrained gait period persisted more prominently overground, indicating a neural adaptation of locomotor control. 

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3. User Impressions and Gait Analysis of Exoskeleton Device Usage in Generalized Tank Farm Activities

   https://doi.org/10.1080/00295639.2024.2316948  

   Bottom, Janelle; Wood, David; Mina, Tamzidul; Bradley, Savannah; Rittikaidachar, Michal; Miera, Alexandria; Wheeler, Jason (March 2024, Nuclear Science and Engineering)

   Tank farm workers involved in nuclear cleanup activities perform physically demanding tasks, typically while wearing heavy personal protective equipment (PPE). Exoskeleton devices have the potential to bring considerable benefit to this industry but have not been thoroughly studied in the context of nuclear cleanup. In this paper, we examine the performance of exoskeletons during a series of tasks emulating jobs performed on tank farms while participants wore PPE commonly deployed by tank farm workers. The goal of this study was to evaluate the effects of commercially available lower-body exoskeletons on a user’s gait kinematics and user perceptions. Three participants each tested three lower-body exoskeletons in a 70-min protocol consisting of level treadmill walking, incline treadmill walking, weighted treadmill walking, a weight lifting session, and a hand tool dexterity task. Results were compared to a no exoskeleton baseline condition and evaluated as individual case studies. The three participants showed a wide spectrum of user preferences and adaptations toward the devices. Individual case studies revealed that some users quickly adapted to select devices for certain tasks while others remained hesitant to use the devices. Temporal effects on gait change and perception were also observed for select participants in device usage over the course of the device session. Device benefit varied between tasks, but no conclusive aggregate trends were observed across devices for all tasks. Evidence suggests that device benefits observed for specific tasks may have been overshadowed by the wide array of tasks used in the protocol. 

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4. Perceived Usefulness of Robotic Technology for Patient Fall Prevention

   https://doi.org/10.1177/21650799241262812  

   Logsdon, M_Cynthia; Kondaurova, Irina; Zhang, Nancy; Das, Sumit; Edwards, Bryan_D; Mitchell, Heather; Nasroui, Olfa; Erdmann, Marjorie; Yu, Hyejin; Alqatamin, Moath; et al (September 2024, Workplace Health & Safety)

   Background:Technology has the potential to prevent patient falls in healthcare settings and to reduce work-related injuries among healthcare providers. However, the usefulness and acceptability of each technology requires careful evaluation. Framed by the Technology Acceptance Model (TAM) and using the Adaptive Robotic Nursing Assistant (ARNA) to assist with patient ambulation, the present study examined the perceived usefulness of robots in patients’ fall prevention with implications for preventing associated work-related injuries among healthcare providers. Methods:Employing an experimental design, subjects were undergraduate nursing students ( N = 38) and one external subject (not a nursing student) who played the role of the patient. Procedures included subjects ambulating a simulated patient in three ways: (a) following the practice of a nurse assisting a patient to walk with the patient wearing a gait belt; (b) an ARNA-assisted process with the gait belt attached to ARNA; (c) an ARNA-assisted process with a subject walking a patient wearing a harness that is attached to ARNA. Block randomization was used with the following experimental scenarios: Gait Belt (human with a gait belt), “ARNA + Gait Belt” (a robot with a gait belt), and “ARNA + Harness” (a robot with a harness). Descriptive statistics and a multiple regression model were used to analyze the data and compare the outcome described as the Perceived Usefulness (PU) of a robot for patient walking versus a human “nurse assistant” without a robot. The independent variables included the experimental conditions of “Gait Belt,” “ARNA + Gait Belt,” and “ARNA + Harness,” the subject’s age, race, and previous videogame playing experience. Findings:Results indicated that PU was significantly higher in the Gait Belt + ARNA and Harness + ARNA conditions than in the Gait Belt condition ( p-value <.01 for both variables). In examining potential influencing factors, the effects of race (White, African American, and Asian), age, and previous video-playing experience were not statistically significant ( p-value >.05). Discussion:Results demonstrated that using robot technology to assist in walking patients was perceived by subjects as more useful in preventing falls than the gait belt. Patient fall prevention also has implications for preventing associated work-related injuries among healthcare providers. Implications:Understanding the effects of a subject’s perceptions can guide further development of assistive robots in patient care. Robotic engineers and interdisciplinary teams can design robots to accommodate worker characteristics and individual differences to improve worker safety and reduce work injuries. 

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5. Design and Preliminary Testing of an Instrumented Exoskeleton for Walking Gait Measurement

   Haque, M.R.; Imtiaz, M.H.; Chou, C.; Sazonov, E.; Shen, X. (April 2019, IEEE SoutheastCon)

   This paper presents the design and preliminary testing of an instrumented exoskeleton system, which is targeted at collecting gait data of the human locomotion to support the controller development of lower-limb wearable robots. This compact and lightweight device features a unique two-degree-of-freedom joint to minimize the interference to the user movement and a simple yet effective adjustment mechanism to fit subjects at different heights. For the gait measurement, the device incorporates embedded joint goniometers to obtain the knee and ankle positions, and inertial measurement units to obtain three-dimensional kinematic information. Force-sensing resistors are also incorporated into the shoe insole for plantar pressure measurement. Sensor signals are routed to an onboard microcontroller system for data storage and transfer, and the system is fully self-contained with onboard battery to facilitate data collection in various environments. A prototype of the exoskeleton was fabricated, and preliminary testing was conducted on two healthy subjects in various postures and modes of movement (walking, sitting, standing, stair climbing, etc.). The evaluation of a temporal event detection test showed no more than 5.5% mean variation in the measure of step counts by the sensory system and video annotation. These results indicate that the exoskeleton can provide an accurate measurement of gait information, using measurements taken from external video recordings as the benchmark in this preliminary validation study. 

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