More Like this

1. Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism

   https://doi.org/10.1002/aur.2391  

   Carpenter, Kimberly L. H. ; Hahemi, Jordan ; Campbell, Kathleen ; Lippmann, Steven J. ; Baker, Jeffrey P. ; Egger, Helen L. ; Espinosa, Steven ; Vermeer, Saritha ; Sapiro, Guillermo ; Dawson, Geraldine ( September 2020 , Autism Research)

   Commonly used screening tools for autism spectrum disorder (ASD) generally rely on subjective caregiver questionnaires. While behavioral observation is more objective, it is also expensive, time‐consuming, and requires significant expertise to perform. As such, there remains a critical need to develop feasible, scalable, and reliable tools that can characterize ASD risk behaviors. This study assessed the utility of a tablet‐based behavioral assessment for eliciting and detecting one type of risk behavior, namely, patterns of facial expression, in 104 toddlers (ASDN= 22) and evaluated whether such patterns differentiated toddlers with and without ASD. The assessment consisted of the child sitting on his/her caregiver's lap and watching brief movies shown on a smart tablet while the embedded camera recorded the child's facial expressions. Computer vision analysis (CVA) automatically detected and tracked facial landmarks, which were used to estimate head position and facial expressions (Positive, Neutral, All Other). Using CVA, specific points throughout the movies were identified that reliably differentiate between children with and without ASD based on their patterns of facial movement and expressions (area under the curves for individual movies ranging from 0.62 to 0.73). During these instances, children with ASD more frequently displayed Neutral expressions compared to children without ASD, who had more All Other expressions. The frequency of All Other expressions was driven by non‐ASD children more often displaying raised eyebrows and an open mouth, characteristic of engagement/interest. Preliminary results suggest computational coding of facial movements and expressions via a tablet‐based assessment can detect differences in affective expression, one of the early, core features of ASD.

   This study tested the use of a tablet in the behavioral assessment of young children with autism. Children watched a series of developmentally appropriate movies and their facial expressions were recorded using the camera embedded in the tablet. Results suggest that computational assessments of facial expressions may be useful in early detection of symptoms of autism.

    

   more » « less
2. Kinematic Trajectories in Response to Speed Perturbations in Walking Suggest Modular Task-Level Control of Leg Angle and Length

   https://doi.org/10.1093/icb/icac057  

   Schwaner, M. J. ; Nishikawa, K. C. ; Daley, M. A. ( May 2022 , Integrative And Comparative Biology)

   Navigating complex terrains requires dynamic interactions between the substrate, musculoskeletal, and sensorimotor systems. Current perturbation studies have mostly used visible terrain height perturbations, which do not allow us to distinguish among the neuromechanical contributions of feedforward control, feedback-mediated, and mechanical perturbation responses. Here, we use treadmill-belt speed perturbations to induce a targeted perturbation to foot speed only, and without terrain-induced changes in joint posture and leg loading at stance onset. Based on previous studies suggesting a proximo-distal gradient in neuromechanical control, we hypothesized that distal joints would exhibit larger changes in joint kinematics, compared to proximal joints. Additionally, we expected birds to use feedforward strategies to increase the intrinsic stability of gait. To test these hypotheses, seven adult guinea fowl were video recorded while walking on a motorized treadmill, during both steady and perturbed trials. Perturbations consisted of repeated exposures to a deceleration and acceleration of the treadmill-belt speed. Surprisingly, we found that joint angular trajectories and center of mass fluctuations remain very similar, despite substantial perturbation of foot velocity by the treadmill belt. Hip joint angular trajectories exhibit the largest changes, with the birds adopting a slightly more flexed position across all perturbed strides. Additionally, we observed increased stride duration across all strides, consistent with feedforward changes in the control strategy. The speed perturbations mainly influenced the timing of stance and swing, with the largest kinematic changes in the strides directly following a deceleration. Our findings do not support the general hypothesis of a proximo-distal gradient in joint control, as distal joint kinematics remain largely unchanged. Instead, we find that leg angular trajectory and the timing of stance and swing are most sensitive to this specific perturbation, and leg length actuation remains largely unchanged. Our results are consistent with modular task-level control of leg length and leg angle actuation, with different neuromechanical control and perturbation sensitivity in each actuation mode. Distal joints appear to be sensitive to changes in vertical loading but not foot fore-aft velocity. Future directions should include in vivo studies of muscle activation and force–length dynamics to provide more direct evidence of the sensorimotor control strategies for stability in response to belt-speed perturbations.

    

   more » « less
3. Corn Snakes Show Consistent Sarcomere Length Ranges Across Muscle Groups and Ontogeny

   https://doi.org/10.1093/iob/obac040  

   Jurestovsky, Derek J. ; Tingle, Jessica L. ; Astley, Henry C. ( September 2022 , Integrative Organismal Biology)

   The force-generating capacity of muscle depends upon many factors including the actin-myosin filament overlap due to the relative length of the sarcomere. Consequently, the force output of a muscle may vary throughout its range of motion, and the body posture allowing maximum force generation may differ even in otherwise similar species. We hypothesized that corn snakes would show an ontogenetic shift in sarcomere length range from being centered on the plateau of the length-tension curve in small individuals to being on the descending limb in adults. Sarcomere lengths across the plateau would be advantageous for locomotion, while the descending limb would be advantageous for constriction due to the increase in force as the coil tightens around the prey. To test this hypothesis, we collected sarcomere lengths from freshly euthanized corn snakes, preserving segments in straight and maximally curved postures, and quantifying sarcomere length via light microscopy. We dissected 7 muscles (spinalis, semispinalis, multifidus, longissimus dorsi, iliocostalis (dorsal and ventral), and levator costae) in an ontogenetic series of corn snakes (mass = 80–335 g) at multiple regions along the body (anterior, middle, and posterior). Our data shows all of the muscles analyzed are on the descending limb of the length-tension curve at rest across all masses, regions, and muscles analyzed, with muscles shortening onto or past the plateau when flexed. While these results are consistent with being advantageous for constriction at all sizes, there could also be unknown benefits of this sarcomere arrangement for locomotion or striking.

    

   more » « less
4. FPGA-based smart chair recognition system using flex sensors

   https://doi.org/10.1109/DCAS53974.2022.9845620  

   AbuTerkia, Ibrahim ; Hannoun, Mustafa ; Suwal, Bikal ; Ahmed, Md Sharif ; Sundaravdivel, Prabha ( June 2022 , IEEE 15th Dallas Circuit And System Conference (DCAS))

   Sitting is the most common status of modern human beings. Many people are sitting with bad posture which may lead to postural pain. Especially for people with short term-disabilities, sitting in the right posture is very important. In this research, we propose a posture recognition system on an office chair that can categorize different health-related sitting postures to prevent harm from bad sitting postures. The smart chair system consists of an array of five flex sensors integrated into an FPGA board. The output of the system is the classification result of the sitting posture. In this paper, several health-related sitting postures are selected. The sitting postures are: 1-sit straight; 2-left recline; 3-right recline; 4-lounge;5-lean backward; 6-cross left leg; 7-cross right leg. The proposed reconfigurable framework will be integrated as part of smart ambient assisted living with user-centered health monitoring system. 

   more » « less
5. Robotic Replica of a Human Spine Uses Soft Magnetic Sensor Array to Forecast Intervertebral Loads and Posture after Surgery

   https://doi.org/10.3390/s22010212  

   Lin, Maohua ; Abd, Moaed A. ; Taing, Alex ; Tsai, Chi-Tay ; Vrionis, Frank D. ; Engeberg, Erik D. ( January 2022 , Sensors)

   Cervical disc implants are conventional surgical treatments for patients with degenerative disc disease, such as cervical myelopathy and radiculopathy. However, the surgeon still must determine the candidacy of cervical disc implants mainly from the findings of diagnostic imaging studies, which can sometimes lead to complications and implant failure. To help address these problems, a new approach was developed to enable surgeons to preview the post-operative effects of an artificial disc implant in a patient-specific fashion prior to surgery. To that end, a robotic replica of a person’s spine was 3D printed, modified to include an artificial disc implant, and outfitted with a soft magnetic sensor array. The aims of this study are threefold: first, to evaluate the potential of a soft magnetic sensor array to detect the location and amplitude of applied loads; second, to use the soft magnetic sensor array in a 3D printed human spine replica to distinguish between five different robotically actuated postures; and third, to compare the efficacy of four different machine learning algorithms to classify the loads, amplitudes, and postures obtained from the first and second aims. Benchtop experiments showed that the soft magnetic sensor array was capable of precisely detecting the location and amplitude of forces, which were successfully classified by four different machine learning algorithms that were compared for their capabilities: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), and Artificial Neural Network (ANN). In particular, the RF and ANN algorithms were able to classify locations of loads applied 3.25 mm apart with 98.39% ± 1.50% and 98.05% ± 1.56% accuracies, respectively. Furthermore, the ANN had an accuracy of 94.46% ± 2.84% to classify the location that a 10 g load was applied. The artificial disc-implanted spine replica was subjected to flexion and extension by a robotic arm. Five different postures of the spine were successfully classified with 100% ± 0.0% accuracy with the ANN using the soft magnetic sensor array. All results indicated that the magnetic sensor array has promising potential to generate data prior to invasive surgeries that could be utilized to preoperatively assess the suitability of a particular intervention for specific patients and to potentially assist the postoperative care of people with cervical disc implants. 

   more » « less