Anthony Giachin, J. J. Steckenrider, Gregory M Freisinger
In this paper, we propose a probabilistic multi-Gaussian parameter estimation technique which addresses the complex relationship between acceleration and ground force signals used to derive a human’s static center of pressure. The intent of this work is to develop an accurate accelerometer-based method for determining postural control and neuromuscular status which is more portable and cost-effective than force plate-based techniques. Acceleration data was collected using an inertial measurement unit while ground reaction forces were simultaneously measured using a force plate. Various metrics were calculated from both sensors and probabilistic data models were built to characterize the relationships between the two sensors. These models were used to predict force-based postural control metrics corresponding to observed acceleration metrics. Data collected from one participant was used as a training set to which the test data of two individuals were then applied. We conclude that converted acceleration-based metrics on average can accurately predict all the corresponding force-based metrics we studied here. Furthermore, the proposed multi-Gaussian parameter estimation approach outperforms a more basic linear transformation technique for 75% of the metrics studied, as evidenced by an increase in correlation coefficients between true and estimated force plate metrics.
{"title":"A Data-Driven Approach for Estimating Postural Control Using an Inertial Measurement Unit","authors":"Anthony Giachin, J. J. Steckenrider, Gregory M Freisinger","doi":"10.1115/imece2021-70518","DOIUrl":"https://doi.org/10.1115/imece2021-70518","url":null,"abstract":"\u0000 In this paper, we propose a probabilistic multi-Gaussian parameter estimation technique which addresses the complex relationship between acceleration and ground force signals used to derive a human’s static center of pressure. The intent of this work is to develop an accurate accelerometer-based method for determining postural control and neuromuscular status which is more portable and cost-effective than force plate-based techniques. Acceleration data was collected using an inertial measurement unit while ground reaction forces were simultaneously measured using a force plate. Various metrics were calculated from both sensors and probabilistic data models were built to characterize the relationships between the two sensors. These models were used to predict force-based postural control metrics corresponding to observed acceleration metrics. Data collected from one participant was used as a training set to which the test data of two individuals were then applied. We conclude that converted acceleration-based metrics on average can accurately predict all the corresponding force-based metrics we studied here. Furthermore, the proposed multi-Gaussian parameter estimation approach outperforms a more basic linear transformation technique for 75% of the metrics studied, as evidenced by an increase in correlation coefficients between true and estimated force plate metrics.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122840408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper provides a brief overview of the advances in the area of early identification of different types of abnormalities and diseases, including respiratory illnesses and cardiovascular diseases, using noninvasive screening of biomedical acoustic signals. These signals include sounds and vibrations generated by different human body organs and systems that can be measured on the body surface using sensors such as stethoscopes and accelerometers. In this study, the measurement methods and signal processing algorithms for customized feature extraction and classification as well as clinical potentials, current limitations, and future directions are briefly reviewed and discussed.
{"title":"Advances in Noninvasive Diagnosis Based on Body Sounds and Vibrations – A Review","authors":"Amirtahà Taebi, F. Khalili","doi":"10.1115/imece2021-73815","DOIUrl":"https://doi.org/10.1115/imece2021-73815","url":null,"abstract":"\u0000 This paper provides a brief overview of the advances in the area of early identification of different types of abnormalities and diseases, including respiratory illnesses and cardiovascular diseases, using noninvasive screening of biomedical acoustic signals. These signals include sounds and vibrations generated by different human body organs and systems that can be measured on the body surface using sensors such as stethoscopes and accelerometers. In this study, the measurement methods and signal processing algorithms for customized feature extraction and classification as well as clinical potentials, current limitations, and future directions are briefly reviewed and discussed.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121347342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Linda Zhu, Nathaniel S. Miller, Charlotte Tang, Sriram Pendyala, Quinn Hanses, Lacie Gladding
Tremor, or an involuntary and oscillatory movement of a body part, is a cardinal symptom of Parkinson’s disease (PD) that can significantly impact activities of daily living in people with PD (PwPD). Although tremor can be mitigated with anti-PD medications, medication effectiveness is mixed for PwPD. Therefore, daily monitoring and assessment of tremor are of interest to PwPD, clinicians, and researchers. While several sensors and wearable devices have been developed and introduced to the consumer market, high costs limit their accessibility. The current research is two-fold. First, an assessment system based on multiple algorithms is developed for evaluating the reliability of measurements of PD symptoms: hand tremor and finger/hand movement speed. Second, an Android mobile application was designed and developed to capture finger-tapping frequencies and measurements of several PD symptoms like hand tremor. A healthy young adult participant produced a self-generated tremor for this study. The participant held the portable device and conducted self-measurements by following in-app instructions. Resting tremor was measured while the participant rested his upper extremity on the arm of a chair, postural tremor was measured while he maintained a position against gravity, and kinetic tremor was measured during a movement task. Data collection took approximately fifteen minutes. The linear and rotational motions, respectively, were collected by accelerometers and gyroscopes embedded within the mobile device. The results were captured and delivered to a cloud database. An assessment system with multiple algorithms provided a final evaluation of the participant’s tremor. The process included three parts. First, calculation of root-mean-square (RMS) values at all linear and rotational directions was conducted to provide tremor strength. Second, fast Fourier transform (FFT) extracted the peak frequency at each direction. The powers of peaks were compared and the highest peak was defined as the dominant frequency and that frequency’s corresponding direction of motion. Third, hand and motion correlation analysis was used to find any coherence of tremor on 3-D motions. To test the reliability of motion measurement, the same motion input was applied to multiple devices simultaneously. The outputs of different types of mobile devices were evaluated, while considering various factors and models of mobile devices in the market (i.e., device size, weight, operating system, sampling frequency, and accuracy during the measurement). Multiple trials were conducted to test the reliability of the assessment system and the performance of the mobile app. Additionally, the mobile application supports finger tapping tests that measure hand movement speed, which is commonly impaired in PwPD. Both tremor and movement speed measurements can be used to evaluate disease progression over time and could support focused medication adjustments based on symptom data.
{"title":"Reliability Check of an Assessment System for Parkinson’s Disease Tremor Monitoring With Portable Devices","authors":"Linda Zhu, Nathaniel S. Miller, Charlotte Tang, Sriram Pendyala, Quinn Hanses, Lacie Gladding","doi":"10.1115/imece2021-71144","DOIUrl":"https://doi.org/10.1115/imece2021-71144","url":null,"abstract":"\u0000 Tremor, or an involuntary and oscillatory movement of a body part, is a cardinal symptom of Parkinson’s disease (PD) that can significantly impact activities of daily living in people with PD (PwPD). Although tremor can be mitigated with anti-PD medications, medication effectiveness is mixed for PwPD. Therefore, daily monitoring and assessment of tremor are of interest to PwPD, clinicians, and researchers. While several sensors and wearable devices have been developed and introduced to the consumer market, high costs limit their accessibility. The current research is two-fold. First, an assessment system based on multiple algorithms is developed for evaluating the reliability of measurements of PD symptoms: hand tremor and finger/hand movement speed. Second, an Android mobile application was designed and developed to capture finger-tapping frequencies and measurements of several PD symptoms like hand tremor.\u0000 A healthy young adult participant produced a self-generated tremor for this study. The participant held the portable device and conducted self-measurements by following in-app instructions. Resting tremor was measured while the participant rested his upper extremity on the arm of a chair, postural tremor was measured while he maintained a position against gravity, and kinetic tremor was measured during a movement task. Data collection took approximately fifteen minutes. The linear and rotational motions, respectively, were collected by accelerometers and gyroscopes embedded within the mobile device. The results were captured and delivered to a cloud database. An assessment system with multiple algorithms provided a final evaluation of the participant’s tremor. The process included three parts. First, calculation of root-mean-square (RMS) values at all linear and rotational directions was conducted to provide tremor strength. Second, fast Fourier transform (FFT) extracted the peak frequency at each direction. The powers of peaks were compared and the highest peak was defined as the dominant frequency and that frequency’s corresponding direction of motion. Third, hand and motion correlation analysis was used to find any coherence of tremor on 3-D motions. To test the reliability of motion measurement, the same motion input was applied to multiple devices simultaneously. The outputs of different types of mobile devices were evaluated, while considering various factors and models of mobile devices in the market (i.e., device size, weight, operating system, sampling frequency, and accuracy during the measurement). Multiple trials were conducted to test the reliability of the assessment system and the performance of the mobile app. Additionally, the mobile application supports finger tapping tests that measure hand movement speed, which is commonly impaired in PwPD. Both tremor and movement speed measurements can be used to evaluate disease progression over time and could support focused medication adjustments based on symptom data.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131107808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Actuators are a vital component, and more often than not one of the limiting factors in robotics and robotics related applications. For the use of actuators in robotics related to humanoids, exoskeletons, prosthetics and orthoses, there are more factors that influence the selected actuator than the basic mechanical outputs, size, backlash, material and power consumption. The main interest within these applications is that because the device is being carried by the human user, thus weight, power consumption and form factor are important selection parameters. The correct selection of an actuator for these applications is a difficult and lengthy process to perform. This paper creates an organizational framework and database for searching the wide range of actuators. This dataset is organized into a design tool that plots the properties of each actuator on varying graphs creating trade-off Ashby charts to rapidly narrow the selection space for designers. A case study is performed to demonstrate the use of this design tool in human-centric actuation applications. The database is utilized in the selection of the ideal actuator based on lines of best fit and a multivariate regression analysis for the optimization of parameters about the required specifications. In addition, a meta-analysis identifies clusters of current actuators, gaps for new developments, and trends. This work provides research direction into developing specific actuators to fit into these trend gaps which offers substantial benefits to humanoids, exoskeletons, prosthetics and orthosis.
{"title":"Development of an Organisational Framework for the Optimal and Efficient Selection of Actuators","authors":"P. Hanna, Marc G. Carmichael, L. Clemon","doi":"10.1115/imece2021-67744","DOIUrl":"https://doi.org/10.1115/imece2021-67744","url":null,"abstract":"\u0000 Actuators are a vital component, and more often than not one of the limiting factors in robotics and robotics related applications. For the use of actuators in robotics related to humanoids, exoskeletons, prosthetics and orthoses, there are more factors that influence the selected actuator than the basic mechanical outputs, size, backlash, material and power consumption. The main interest within these applications is that because the device is being carried by the human user, thus weight, power consumption and form factor are important selection parameters. The correct selection of an actuator for these applications is a difficult and lengthy process to perform. This paper creates an organizational framework and database for searching the wide range of actuators. This dataset is organized into a design tool that plots the properties of each actuator on varying graphs creating trade-off Ashby charts to rapidly narrow the selection space for designers. A case study is performed to demonstrate the use of this design tool in human-centric actuation applications. The database is utilized in the selection of the ideal actuator based on lines of best fit and a multivariate regression analysis for the optimization of parameters about the required specifications. In addition, a meta-analysis identifies clusters of current actuators, gaps for new developments, and trends. This work provides research direction into developing specific actuators to fit into these trend gaps which offers substantial benefits to humanoids, exoskeletons, prosthetics and orthosis.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133648921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sachin Govil, Nickolas Forsch, Sara Salehyar, K. Gilbert, Avan Suinesiaputra, S. Hegde, J. Perry, A. Young, J. Omens, A. McCulloch
Patients with repaired tetralogy of Fallot (rTOF) are at risk of long-term left ventricular (LV) dysfunction associated with poor outcomes. In this study, we examined the association of LV end-diastolic (ED) shape with components of systolic wall motion (SWM) that contribute to global systolic dysfunction in an rTOF patient cohort. Features of LV shape associated with conicity and septal wall curvature correlated with components of SWM. The effect of ED shape perturbations on SWM were examined in a finite element analysis of systolic ventricular mechanics. Variations in the combination of ED shape and myocardial contractility were able to match predicted measures of SWM. From these results, we hypothesize that greater LV conicity and a flatter septal wall are markers of reduced global myocardial contractility and should be examined further for clinical prognostic utility to improve patient outcomes.
{"title":"Morphological Markers and Determinants of Left Ventricular Systolic Dysfunction in Repaired Tetralogy of Fallot","authors":"Sachin Govil, Nickolas Forsch, Sara Salehyar, K. Gilbert, Avan Suinesiaputra, S. Hegde, J. Perry, A. Young, J. Omens, A. McCulloch","doi":"10.1115/imece2021-70591","DOIUrl":"https://doi.org/10.1115/imece2021-70591","url":null,"abstract":"\u0000 Patients with repaired tetralogy of Fallot (rTOF) are at risk of long-term left ventricular (LV) dysfunction associated with poor outcomes. In this study, we examined the association of LV end-diastolic (ED) shape with components of systolic wall motion (SWM) that contribute to global systolic dysfunction in an rTOF patient cohort. Features of LV shape associated with conicity and septal wall curvature correlated with components of SWM. The effect of ED shape perturbations on SWM were examined in a finite element analysis of systolic ventricular mechanics. Variations in the combination of ED shape and myocardial contractility were able to match predicted measures of SWM. From these results, we hypothesize that greater LV conicity and a flatter septal wall are markers of reduced global myocardial contractility and should be examined further for clinical prognostic utility to improve patient outcomes.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123277273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mihai Dragusanu, Z. Iqbal, D. Prattichizzo, M. Malvezzi
Nowadays, the rehabilitation process can significantly increase the efficacy exploiting the potentialities of robot-mediated therapies. Robot rehabilitation is an emerging and promising topic that incorporates robotics with neuroscience and rehabilitation to define new methods for supporting patients with neurological diseases. In this paper we present the design of an innovative exoskeleton for hand finger flexion/extension motion rehabilitation and training. It is designed to be modular, wearable, and easy to control and manage. It can be used by the patient in collaboration with the therapist or autonomously. The paper introduces the main steps of device design and development and presents and compare three different solutions.
{"title":"Design of a Modular Hand Exoskeleton for Rehabilitation and Training","authors":"Mihai Dragusanu, Z. Iqbal, D. Prattichizzo, M. Malvezzi","doi":"10.1115/imece2021-70343","DOIUrl":"https://doi.org/10.1115/imece2021-70343","url":null,"abstract":"\u0000 Nowadays, the rehabilitation process can significantly increase the efficacy exploiting the potentialities of robot-mediated therapies. Robot rehabilitation is an emerging and promising topic that incorporates robotics with neuroscience and rehabilitation to define new methods for supporting patients with neurological diseases. In this paper we present the design of an innovative exoskeleton for hand finger flexion/extension motion rehabilitation and training. It is designed to be modular, wearable, and easy to control and manage. It can be used by the patient in collaboration with the therapist or autonomously. The paper introduces the main steps of device design and development and presents and compare three different solutions.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122181395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Micro-, and milli-scale robots have emerged as next generation of intelligent technology for minimally invasive diagnosis and treatment. Recent minimally invasive interventions call for robots that work as tiny “surgeons” or drug delivery “vehicles” to achieve inner body diagnostic, surgical, and therapeutic practices, without any trauma or discomfort. Most traditional medical robots are large, and lack effective locomotion design, which prevent them from entering small entrances and moving smoothly in small working areas, such as long and narrow passages. Presented in this paper is a design of an innovative milli-scale deployable tensegrity microrobot for minimally invasive interventions. The robot is made of a deployable tensegrity structure integrated by self-stress. A folded size of the robot is small for easily entering a desired working area with a small entrance. When deployed, the tensegrity body of the robot displays lightweight and high stiffness to sustain loads and prevent damages when burrowing through tightly packed tissues or high-pressure environments. Locomotion of the tensegrity microrobot is designed to mimic a crawling motion of an earthworm, which grants the robot an ability to move well through small working areas. The robot is also an untethered agent. Morphing for deployment and locomotion of the robot is actuated by magnetic forces generated by its active members that serve as electromagnetic coils.
{"title":"A Deployable Tensegrity Microrobot for Minimally Invasive Interventions","authors":"S. Yuan, Wuming Jing, Hao Jiang","doi":"10.1115/imece2021-67009","DOIUrl":"https://doi.org/10.1115/imece2021-67009","url":null,"abstract":"\u0000 Micro-, and milli-scale robots have emerged as next generation of intelligent technology for minimally invasive diagnosis and treatment. Recent minimally invasive interventions call for robots that work as tiny “surgeons” or drug delivery “vehicles” to achieve inner body diagnostic, surgical, and therapeutic practices, without any trauma or discomfort. Most traditional medical robots are large, and lack effective locomotion design, which prevent them from entering small entrances and moving smoothly in small working areas, such as long and narrow passages. Presented in this paper is a design of an innovative milli-scale deployable tensegrity microrobot for minimally invasive interventions. The robot is made of a deployable tensegrity structure integrated by self-stress. A folded size of the robot is small for easily entering a desired working area with a small entrance. When deployed, the tensegrity body of the robot displays lightweight and high stiffness to sustain loads and prevent damages when burrowing through tightly packed tissues or high-pressure environments. Locomotion of the tensegrity microrobot is designed to mimic a crawling motion of an earthworm, which grants the robot an ability to move well through small working areas. The robot is also an untethered agent. Morphing for deployment and locomotion of the robot is actuated by magnetic forces generated by its active members that serve as electromagnetic coils.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117226416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. González-Navarrete, A. Vidal-Lesso, Hector PLASCENCIA MORA, Xavier Ulises Huerta-Jacobo
The aim of this work is to propose a viscoelastic material model for human cartilage tissue that allows simulating its structural stiffness and elastic strain energy that absorbs per unit volume. For this, experimental data reported from flat cylindrical indentation test on human samples of seven patients with unicompartmental osteoarthritis (N = 7) were used. These data allowed the use of one linear model and the adjustment of two non-linear material models, a visco-hypoelastic (VE) and a visco-hyperelastic (VHE) model. The finite element models for the indentation test considered the indenter as a rigid body, the cartilage and subchondral bone as deformable bodies. The indentation force (F, material model structural reaction) and resilience modulus (Er, elastic strain energy per unit volume) were considered as validation parameters. The results suggest that largest differences respect to experimental data were found with the linear model (up to 44.33% for Er and 21.75% for F). The best model to reproduce the indentation force was the VHE (mean difference of 3.37±1.03%), while for the elastic strain energy per unit volume, the best model was the VE (mean difference of 16.65±12.74%).
{"title":"A Comparison of Visco-Hypoelastic and Visco-Hyperelastic Model to Predict the Elastic Strain Energy for Articular Cartilage of Knee Joint","authors":"R. González-Navarrete, A. Vidal-Lesso, Hector PLASCENCIA MORA, Xavier Ulises Huerta-Jacobo","doi":"10.1115/imece2021-69494","DOIUrl":"https://doi.org/10.1115/imece2021-69494","url":null,"abstract":"\u0000 The aim of this work is to propose a viscoelastic material model for human cartilage tissue that allows simulating its structural stiffness and elastic strain energy that absorbs per unit volume.\u0000 For this, experimental data reported from flat cylindrical indentation test on human samples of seven patients with unicompartmental osteoarthritis (N = 7) were used. These data allowed the use of one linear model and the adjustment of two non-linear material models, a visco-hypoelastic (VE) and a visco-hyperelastic (VHE) model. The finite element models for the indentation test considered the indenter as a rigid body, the cartilage and subchondral bone as deformable bodies. The indentation force (F, material model structural reaction) and resilience modulus (Er, elastic strain energy per unit volume) were considered as validation parameters.\u0000 The results suggest that largest differences respect to experimental data were found with the linear model (up to 44.33% for Er and 21.75% for F). The best model to reproduce the indentation force was the VHE (mean difference of 3.37±1.03%), while for the elastic strain energy per unit volume, the best model was the VE (mean difference of 16.65±12.74%).","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121715670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brandon A. Brown, R. Daniel, V. Chancey, Tyler F. Rooks
Environmental sensors (ES) are a proposed way to identify potentially concussive events using Rigid Body Kinematics (RBK) to get motion at the head CG. This study systematically investigated the extent that errors in RBK assumptions including sensor orientation (SO), head CG position (HCGP), and exposure severity contribute to errors in sensor readings of predicted peak resultant linear acceleration (PRLA) at the head CG. Simulated sensor readings were defined by idealized representations of head motion [extension, lateral bending and axial rotation] using a half sine pulse for linear and angular acceleration. Peak magnitudes of linear acceleration ranged from 12.5 to 100 Gs and peak magnitudes of angular acceleration ranged from 1250 to 10000 rad/s/s. Durations of linear and angular accelerations ranged between 5 and 30 ms. Simulated HCGP variations ranged from −10% to 10% radius of the head (assumed to be a sphere) in each direction and SO variations ranged from −20 to 20 degrees about each axis. True head CG response was calculated using zero error for SO and HCGP. Mean (+/− standard deviation) of calculated errors for maximum percent error (MaxPE) of a given head exposure was 30.3% (+/−9.71). 50% and 38% of all simulated exposures had MaxPE associated with maximum SO and HCGP offset, respectively. MaxPE was likely due to user error, ES form factor, and anthropometric variation.
{"title":"Parametric Evaluation of Head Center of Gravity Acceleration Error From Rigid Body Kinematics Assumptions Used in Environmental Sensors","authors":"Brandon A. Brown, R. Daniel, V. Chancey, Tyler F. Rooks","doi":"10.1115/imece2021-69334","DOIUrl":"https://doi.org/10.1115/imece2021-69334","url":null,"abstract":"\u0000 Environmental sensors (ES) are a proposed way to identify potentially concussive events using Rigid Body Kinematics (RBK) to get motion at the head CG. This study systematically investigated the extent that errors in RBK assumptions including sensor orientation (SO), head CG position (HCGP), and exposure severity contribute to errors in sensor readings of predicted peak resultant linear acceleration (PRLA) at the head CG. Simulated sensor readings were defined by idealized representations of head motion [extension, lateral bending and axial rotation] using a half sine pulse for linear and angular acceleration. Peak magnitudes of linear acceleration ranged from 12.5 to 100 Gs and peak magnitudes of angular acceleration ranged from 1250 to 10000 rad/s/s. Durations of linear and angular accelerations ranged between 5 and 30 ms. Simulated HCGP variations ranged from −10% to 10% radius of the head (assumed to be a sphere) in each direction and SO variations ranged from −20 to 20 degrees about each axis. True head CG response was calculated using zero error for SO and HCGP. Mean (+/− standard deviation) of calculated errors for maximum percent error (MaxPE) of a given head exposure was 30.3% (+/−9.71). 50% and 38% of all simulated exposures had MaxPE associated with maximum SO and HCGP offset, respectively. MaxPE was likely due to user error, ES form factor, and anthropometric variation.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126382997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work deals with the stability of the dynamics of human gait. This is a common exercise. The focus of this investigation is to analyze the knee angle time series and calculate the divergence for over-ground and treadmill walking. Experiments using motion capture technology are used to capture the movement. MATLAB software package is used to calculate the Lyapunov Exponents from the time series. Results are compared with similar studies in the literature. This work provides an insight on the level of stability for treadmill walking. A comparison with stability of normal gait might give an insight on how the treadmill can facilitate rehabilitation using gait.
{"title":"Gait Stability Using Lyapunov Exponents","authors":"J. Galarza, D. Caruntu, S. Vásquez, R. Freeman","doi":"10.1115/imece2021-73242","DOIUrl":"https://doi.org/10.1115/imece2021-73242","url":null,"abstract":"\u0000 This work deals with the stability of the dynamics of human gait. This is a common exercise. The focus of this investigation is to analyze the knee angle time series and calculate the divergence for over-ground and treadmill walking. Experiments using motion capture technology are used to capture the movement. MATLAB software package is used to calculate the Lyapunov Exponents from the time series. Results are compared with similar studies in the literature. This work provides an insight on the level of stability for treadmill walking. A comparison with stability of normal gait might give an insight on how the treadmill can facilitate rehabilitation using gait.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127448652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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