Blynn Shideler grew up in Pittsburgh and managed a local Dunkin Donuts before starting college at Washington & Jefferson College. At Washington & Jefferson, he wrestled in the 2015 NCAA D-III national team championships and studied neurological movement disorders as a Magellan Scholar at the University of Paris. Blynn earned a B.A. in physics & French from Washington & Jefferson before enrolling in a dual degree program at Columbia University. At Columbia, Blynn sang for the Columbia Chamber Choir, volunteered in the Mount Sinai St. Luke’s Hospital Emergency Department, and developed medical robotics with the Columbia Robotics & Rehabilitation Laboratory while pursuing a B.S. in biomedical engineering. Throughout his undergraduate studies, Blynn spent a summer as a visiting student at McGill University and completed several global research fellowships, including positions at Hangzhou Dianzi University and Victoria University of Melbourne, where he studied medical robotics and developed technologies for pediatric physical disabilities. Blynn is the lead inventor on multiple patent applications for assistive technologies to help children with movement disorders.
After graduating from Columbia in 2019, Blynn spent a year at the NIH Clinical Center’s Rehabilitation Medicine Department working on the NIH exoskeleton for pediatric cerebral palsy. During his year at NIH, Blynn also volunteered as the Varsity Wrestling Coach at Rockville High School. Blynn’s most recent research paper with the NIH shows the potential benefits of using neuromuscular electrical stimulation for improving walking biomechanics in children with crouch gait. Blynn’s long-term goal in medicine is to pursue a career in pediatric rehabilitation and continue developing assistive devices for children with motor disabilities. In his free time, he enjoys walking dogs on Wag Walking and live-streaming Runescape on Twitch.
Professional Affiliations and Activities
Member, American Academy of Physical Medicine & Rehabilitation (AAPM&R) (2021 - Present)
Phi Beta Kappa, Member
Education & Certifications
Bachelor of Arts, Washington & Jefferson College (2019)
Bachelor of Science, Columbia University (2019)
Visiting Student, McGill University, French (2016)
Preetha Basaviah, E4C Mentor
Service, Volunteer and Community Work
Emergency Medicine Department Volunteer, Mount Sinai St. Luke's Hospital (October 2017 - May 2019)
Supervisor: Amy Bush from Department of Volunteer Services
New York, NY
Blynn Shideler, Simon Taylor, Rezaul Begg. "United States Patent 10,722,149 Real-Time Biofeedback Rehabilitation Tool Guiding and Illustrating Foot Placement for Gait Training", Victoria University, Jul 28, 2020
Blynn Shideler, Elizabeth Shrout, Katherine Cavanaugh, Rachel Alexander, Maxime Robert. "United States Patent 62890265 Limb Motion Tracking Biofeedback Platform and Method of Rehabilitation Therapy for Patients with Spasticity", The Trustees of Columbia University in the City of New York, Aug 22, 2019
Biomedical Engineering Research Fellow, University of Paris (May 2015 - August 2015)
PI: Pierre-Paul Vidal, MD, PhD & Visiting Scholar Ming Meng, PhD from Cognition & Action Group
Visiting Student of Research, Hangzhou Dianzi University (May 2016 - July 2016)
PI: Ming Meng, PhD from the Department of Biomedical Engineering & Instrumentation
Hangzhou, Zhejiang, China
Visiting Research Fellow, Victoria University (May 2017 - August 2017)
PI: Simon Taylor, PhD & Rezaul Begg, PhD from the Institute of Sports, Exercise, and Active Living (ISEAL)
Undergraduate Researcher, Columbia Robotics & Rehabilitation Laboratory (October 2017 - May 2019)
PI: Sunil Agrawal, PhD from the Robotics and Rehabilitation (ROAR) Laboratory
New York, NY
IRTA Research Fellow, National Institutes of Health (June 2019 - July 2020)
PI: Diane Damiano, PT, PhD & Thomas Bulea from the National Institutes of Health Clinical Center, Rehabilitation Medicine Department, Functional & Applied Biomechanics Section
Toward a hybrid exoskeleton for crouch gait in children with cerebral palsy: neuromuscular electrical stimulation for improved knee extension.
Journal of neuroengineering and rehabilitation
2020; 17 (1): 121
Neuromuscular Electrical Stimulation (NMES) has been utilized for many years in cerebral palsy (CP) with limited success despite its inherent potential for improving muscle size and/or strength, inhibiting or reducing spasticity, and enhancing motor performance during functional activities such as gait. While surface NMES has been shown to successfully improve foot drop in CP and stroke, correction of more complex gait abnormalities in CP such as flexed knee (crouch) gait remains challenging due to the level of stimulation needed for the quadriceps muscles that must be balanced with patient tolerability and the ability to deliver NMES assistance at precise times within a gait cycle.This paper outlines the design and evaluation of a custom, noninvasive NMES system that can trigger and adjust electrical stimulation in real-time. Further, this study demonstrates feasibility of one possible application for this digitally-controlled NMES system as a component of a pediatric robotic exoskeleton to provide on-demand stimulation to leg muscles within specific phases of the gait cycle for those with CP and other neurological disorders who still have lower limb sensation and volitional control. A graphical user interface was developed to digitally set stimulation parameters (amplitude, pulse width, and frequency), timing, and intensity during walking. Benchtop testing characterized system delay and power output. System performance was investigated during a single session that consisted of four overground walking conditions in a 15-year-old male with bilateral spastic CP, GMFCS Level III: (1) his current Ankle-Foot Orthosis (AFO); (2) unassisted Exoskeleton; (3) NMES of the vastus lateralis; and (4) NMES of the vastus lateralis and rectus femoris. We hypothesized in this participant with crouch gait that NMES triggered with low latency to knee extensor muscles during stance would have a modest but positive effect on knee extension during stance.The system delivers four channels of NMES with average delays of 16.5 ± 13.5 ms. Walking results show NMES to the vastus lateralis and rectus femoris during stance immediately improved mean peak knee extension during mid-stance (p = 0.003*) and total knee excursion (p = 0.009*) in the more affected leg. The electrical design, microcontroller software and graphical user interface developed here are included as open source material to facilitate additional research into digitally-controlled surface stimulation ( github.com/NIHFAB/NMES ).The custom, digitally-controlled NMES system can reliably trigger electrical stimulation with low latency. Precisely timed delivery of electrical stimulation to the quadriceps is a promising treatment for crouch. Our ultimate goal is to synchronize NMES with robotic knee extension assistance to create a hybrid NMES-exoskeleton device for gait rehabilitation in children with flexed knee gait from CP as well as from other pediatric disorders.clinicaltrials.gov, ID: NCT01961557 . Registered 11 October 2013; Last Updated 27 January 2020.
View details for DOI 10.1186/s12984-020-00738-7
View details for PubMedID 32883297
View details for PubMedCentralID PMC7469320
Overground gait training using virtual reality aimed at gait symmetry.
Human movement science
2021; 76: 102770
This study investigated if training in a virtual reality (VR) environment that provides visual and audio biofeedback on foot placement can induce changes to spatial and temporal parameters of gait during overground walking. Eighteen healthy young adults walked for 23 min back and forth on an instrumented walkway in three different conditions: (i) real environment (RE), (ii) virtual environment (VE) with no biofeedback, and (iii) VE with biofeedback. Visual and audio biofeedback while stepping on virtual footprint targets appearing along a straight path encouraged participants to walk with an asymmetrical step length (SL). A repeated-measures, one-way ANOVA, followed by a pairwise comparison post-hoc analysis with Bonferroni's correction, was performed to compare the step length difference (SLD), stance phase percentage difference (SPPD), and double-support percentage difference (DSPD) between early and late phases of all walking conditions. The results demonstrate the efficacy of the VE biofeedback system for training asymmetrical gait patterns. Participants temporarily adapted an asymmetrical gait pattern immediately post-training in the VE. Induced asymmetries persisted significantly while later walking in the RE. Asymmetry was significant in the spatial parameters of gait (SLD) but not in the temporal parameters (SPPD and DSPD). This paper demonstrates a method to induce unilateral changes in spatial parameters of gait using a novel VR tool. This study provides a proof-of-concept validation that VR biofeedback training can be conducted directly overground and could potentially provide a new method for treatment of hemiplegic gait or asymmetrical walking.
View details for DOI 10.1016/j.humov.2021.102770
View details for PubMedID 33636570
An open source graphical user interface for wireless communication and operation of wearable robotic technology
JOURNAL OF REHABILITATION AND ASSISTIVE TECHNOLOGIES ENGINEERING
2020; 7: 2055668320964056
Wearable robotic exoskeletons offer the potential to move gait training from the clinic to the community thereby providing greater therapy dosage in more naturalistic settings. To capitalize on this potential, intuitive and robust interfaces are necessary between robotic devices and end users. Such interfaces hold great promise for research if they are also designed to record data from the robot during its use.We present the design and validation of an open source graphical user interface (GUI) for wireless operation of and real-time data logging from a pediatric robotic exoskeleton. The GUI was designed for trained users such as an engineer or clinician. A simplified mobile application is also provided to enable exoskeleton operation by an end-user or their caretaker. GUI function was validated during simulated walking with the exoskeleton using a motion capture system.Our results demonstrate the ability of the GUI to wirelessly operate and save data from exoskeleton sensors with high fidelity comparable to motion capture.The GUI code, available in a public repository with a detailed description and step-by-step tutorial, is configurable to interact with any robotic device operated by a microcontroller and therefore represents a potentially powerful tool for deployment and evaluation of community based robotics.
View details for DOI 10.1177/2055668320964056
View details for Web of Science ID 000600032300001
View details for PubMedID 33403122
View details for PubMedCentralID PMC7739088
Age effects on step adaptation during treadmill walking with continuous step length biofeedback
GAIT & POSTURE
2020; 80: 174–77
The inability to adjust step length can lead to falls in older people when navigating everyday terrain. Precisely targeted forward placement of the leading foot, constituting step length adjustment, is required for adaptive gait control, but this ability may reduce with ageing. The objective of this study was to investigate ageing effects on step length adaptation using real-time biofeedback.Does ageing affect the ability to adapt step length to match a target using real-time biofeedback?Fifteen older adults (67 ± 3 years; 8 females) and 27 young adults (24 ± 4 years; 13 females) completed a step length adaptation test while walking at preferred speed on a treadmill. The test involved walking while viewing a monitor at the front of the treadmill that showed a real-time signal of absolute left-right foot displacement. The task was to match the local maxima of the signal (i.e. step length) to two target conditions, at 10 % longer or 10 % shorter than mean baseline step length. When the target was displayed, it remained unchanged for a set of 10 consecutive step attempts. Three sets of 10 attempts for each target condition were allocated in random order, for a total of 30 step attempts per target. Average absolute error and average error (bias) of step length accuracy was computed for each target condition and compared between groups.The step adaptation test identified that older adults had greater mean absolute error for both short and long step targets and showed a step length-dependent bias significantly different to the young.Real-time foot position feedback could be a useful tool to train and evaluate step adaptation in older people.
View details for DOI 10.1016/j.gaitpost.2020.04.027
View details for Web of Science ID 000548457100031
View details for PubMedID 32521471
- Age effects on step adaptation during treadmill walking with continuous step length biofeedback Gait & Posture 2020; 80: 174-177
- A flexible real-time biofeedback tool that trains gait adaptability World Congress of the International Society of Biomechanics Research Gate. 2019
- Real-time biofeedback rehabilitation tool guiding and illustrating foot placement for gait training United States Patent Application Publication 2017
An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis
2016; 11 (10): e0164975
For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor's office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient's home.
View details for DOI 10.1371/journal.pone.0164975
View details for Web of Science ID 000389009200032
View details for PubMedID 27776168
View details for PubMedCentralID PMC5077168