Miniature C-arm simulator using wireless accelerometer based tracking

Author(s):  
Daniel R. Allen ◽  
John T. Moore ◽  
Abigayel Joschko ◽  
Collin Clarke ◽  
Terry M. Peters ◽  
...  
2011 ◽  
Vol 11 (03) ◽  
pp. 471-513 ◽  
Author(s):  
ROBERT LEMOYNE ◽  
TIMOTHY MASTROIANNI ◽  
CRISTIAN COROIAN ◽  
WARREN GRUNDFEST

The deep tendon reflex is a fundamental aspect of a neurological examination. The two major parameters of the tendon reflex are response and latency, which are presently evaluated qualitatively during a neurological examination. The reflex loop is capable of providing insight into the status and therapy response of both upper and lower motor neuron syndromes. Attempts have been made to ascertain reflex response and latency; however, these systems are relatively complex, resource intensive, with issues of consistent and reliable accuracy. The solution presented is a wireless quantified reflex device using tandem three-dimensional (3D) wireless accelerometers to obtain response based on acceleration waveform amplitude and latency derived from temporal acceleration waveform disparity. Three specific aims have been established for the proposed wireless quantified reflex device: (1) Demonstrate the wireless quantified reflex device is reliably capable of ascertaining quantified reflex response and latency using a quantified input. (2) Evaluate the precision of the device using an artificial reflex system. (3) Conduct a longitudinal study respective of subjects with healthy patellar tendon reflexes, using the wireless quantified reflex evaluation device to obtain quantified reflex response and latency. Aim 1 has led to a steady evolution of the wireless quantified reflex device from a singular 2D wireless accelerometer capable of measuring reflex response to a tandem 3D wireless accelerometer capable of reliably measuring reflex response and latency. The hypothesis for aim 1 is that a reflex quantification device can be established for reliably measuring reflex response and latency for the patellar tendon reflex, comprised of an integrated system of wireless 3D MEMS accelerometers. Aim 2 further emphasized the reliability of the wireless quantified reflex device by evaluating an artificial reflex system. The hypothesis for aim 2 is that the wireless quantified reflex device can obtain reliable reflex parameters (response and latency) from an artificial reflex device. Aim 3 synthesizes the findings relevant to aim 1 and 2, while applying the wireless accelerometer reflex quantification device to a longitudinal study of healthy patellar tendon reflexes. The hypothesis for aim 3 is that during a longitudinal evaluation of the deep tendon reflex the parameters for reflex response and latency can be measured with a considerable degree of accuracy, reliability, and reproducibility. Enclosed is a detailed description of a wireless quantified reflex device with research findings and potential utility of the system, inclusive of a comprehensive description of tendon reflexes, prior reflex quantification systems, and correlated applications.


Sensors ◽  
2018 ◽  
Vol 18 (1) ◽  
pp. 262 ◽  
Author(s):  
Li Zhu ◽  
Yuguang Fu ◽  
Raymond Chow ◽  
Billie Spencer ◽  
Jong Park ◽  
...  

2013 ◽  
Vol 02 (02) ◽  
pp. 62-67 ◽  
Author(s):  
Robert LeMoyne ◽  
Timothy Mastroianni ◽  
Warren Grundfest

2018 ◽  
Vol 3 (3) ◽  
pp. 2473011418S0005
Author(s):  
Erin Futrell ◽  
Irene Davis

Category: Sports Introduction/Purpose: Vertical impact forces are highly influenced by the way the foot contacts the ground. These impact forces are associated with high loading rates which have been related to running injuries. As a result, clinicians have begun to use gait retraining interventions to reduce loadrates and prevent future impact-related injuries. Two types of gait retraining techniques have been promoted to reduce excessive running impacts. The first involves increasing cadence (CAD), or number of steps per minute, by 5-10%, thereby reducing stride length. The second type of gait retraining involves landing on the ball of the foot at ground contact, or using a forefoot strike (FFS). Both of these gait-retraining styles have been reported to reduce impacts, but they have not been compared with each other. Methods: 33 healthy runners (9M, 24F), running 5-15 mpw, with a rearfoot strike pattern with cadence < 170 steps/min were recruited. Subjects were randomly allocated to either FFS or CAD retraining. All subjects underwent an 8-session gait retraining program (over 2-3 wks) with auditory feedback on a treadmill. The CAD group ran to a digital metronome to increase cadence by 7.5%. The FFS group wore a wireless accelerometer that provided an auditory signal on footstrike pattern. A gait analysis was conducted at baseline, 1 wk, 1 month, and 6 months. Variables included vertical average and instantaneous load rates (VALR, VILR). A 2 x 4 repeated measures ANOVA was used to compare differences within and between the CAD and FFS groups at baseline, 1 week, 1 month and 6 months post retraining. For variables with significant interactions, simple main effects of group, as well as time were further explored using one-way ANOVA Results: There were significant interaction effects of time*group for VALR (p= 0.001), VILR (p=0.001) and foot angle (p< 0.001), but not cadence. For the simple main effects for the CAD group, VALR reduced by 14%, 7% and 16% at 1 week, 1 month, and 6 months post gait retraining respectively, compared with baseline (Figure 1). However, these reductions were not significant. For the FFS group, VALR was significantly reduced by 50%, 51% and 51% at 1 week, 1 month, and 6 months post gait retraining respectively. Interestingly, both the CAD and FFS groups increased cadence by similar amounts. Conclusion: Transitioning to a FFS pattern is significantly more effective than increasing CAD when reducing vertical loadrate (both VALR and VILR) is the goal. These changes persisted out to 6 months post gait retraining, suggesting permanence of the new pattern.


2016 ◽  
Vol 241 ◽  
pp. 113-119 ◽  
Author(s):  
Zhiyuan Shen ◽  
Chin Yaw Tan ◽  
Kui Yao ◽  
Lei Zhang ◽  
Yi Fan Chen

2014 ◽  
Vol 46 ◽  
pp. 699
Author(s):  
Jessica Dicke ◽  
Nathan Saunders ◽  
Panagiotis Koutakis ◽  
Deborah A. Kegelmeyer ◽  
Anne D. Kloos ◽  
...  

2010 ◽  
Vol 16 (34) ◽  
pp. 1187-1192
Author(s):  
Shinya MATSUMOTO ◽  
Eiji MOTOKAWA ◽  
Daiji FUJII ◽  
Kazuhiko OHTA ◽  
Suenori ARINAGA ◽  
...  

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