scholarly journals OpenSim Moco: Musculoskeletal optimal control

2020 ◽  
Vol 16 (12) ◽  
pp. e1008493
Author(s):  
Christopher L. Dembia ◽  
Nicholas A. Bianco ◽  
Antoine Falisse ◽  
Jennifer L. Hicks ◽  
Scott L. Delp
Keyword(s):  
Motion Tracking ◽  
Model Fitting ◽  
Assistive Device ◽  
Direct Collocation ◽  
Complex Anatomy ◽  
Musculoskeletal Models ◽  
Wide Range ◽  
Walking Motion ◽  
Tracking Motion ◽  
Kinematic Loops

Musculoskeletal simulations are used in many different applications, ranging from the design of wearable robots that interact with humans to the analysis of patients with impaired movement. Here, we introduce OpenSim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation. Moco frees researchers from implementing direct collocation themselves—which typically requires extensive technical expertise—and allows them to focus on their scientific questions. The software can handle a wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which enable modeling of kinematic loops (e.g., cycling models) and complex anatomy (e.g., patellar motion). To show the abilities of Moco, we first solved for muscle activity that produced an observed walking motion while minimizing squared muscle excitations and knee joint loading. Next, we predicted how muscle weakness may cause deviations from a normal walking motion. Lastly, we predicted a squat-to-stand motion and optimized the stiffness of an assistive device placed at the knee. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand the movement of humans and other animals.

scholarly journals OpenSim Moco: Musculoskeletal optimal control

2019 ◽  
Author(s):  
Christopher L. Dembia ◽  
Nicholas A. Bianco ◽  
Antoine Falisse ◽  
Jennifer L. Hicks ◽  
Scott L. Delp
Keyword(s):  
Motion Tracking ◽  
Animal Movement ◽  
Model Fitting ◽  
Direct Collocation ◽  
Musculoskeletal Models ◽  
Wide Range ◽  
Walking Motion ◽  
Tracking Motion ◽  
And Control ◽  
Scientific Questions

AbstractMusculoskeletal simulations of movement can provide insights needed to help humans regain mobility after injuries and design robots that interact with humans. Here, we introduce Open-Sim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation but requires extensive technical expertise to implement. Moco frees researchers from implementing direct collocation themselves, allowing them to focus on their scientific questions. The software can handle the wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which are common in musculoskeletal models. To show Moco’s abilities, we first solve for muscle activity that produces an observed walking motion while minimizing muscle excitations and knee joint loading. Then, we predict a squat-to-stand motion and optimize the stiffness of a passive assistive knee device. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand human and animal movement.

Improving sit-to-stand transition by the saddle-assistive device in the spinal cord injury: A case study

2021 ◽  
pp. 095441192110033
Author(s):  
Akbar Hojjati Najafabadi ◽  
Saeid Amini ◽  
Farzam Farahmand
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Lower Limb ◽  
Reaction Force ◽  
Assistive Device ◽  
Limb Weakness ◽  
Sit To Stand ◽  
Lower Limb Weakness ◽  
Wide Range ◽  
Cord Injury

Physical problems caused by fractures, aging, stroke, and accidents can reduce foot power; these, in the long term, can dwindle the muscles of the waist, thighs, and legs. These conditions provide the basis for the invalidism of the harmed people. In this study, a saddle-walker was designed and evaluated to help people suffering from spinal cord injury and patients with lower limb weakness. This S-AD works based on body weight support against the previously report designs. This saddle-walker consisted of a non-powered four-wheel walker helping to walk and a powered mechanism for the sit-to-stand (STS) transfer. A set of experiments were done on the STS in the use of the standard walker and the saddle-assistive device(S-AD). A comparison of the results showed that this device could reduce the vertical ground reaction force (GRF) of the legs up to 70%. Using this device could help a wide range of patients with lower limb weakness and SCI patients in changing from sitting to standing.

scholarly journals Comparison of Round Window Anatomy between Pediatric and Adult Population: A Perspective from Cochlear Implantation Surgery

2020 ◽  
Vol 42 (3) ◽  
pp. 23-25
Author(s):  
Rabindra B Pradhananga ◽  
Bigyan R Gyawali ◽  
Pabina Rayamajhi
Keyword(s):  
Cochlear Implantation ◽  
Adult Population ◽  
Round Window ◽  
Round Window Membrane ◽  
Institute Of Medicine ◽  
Statistical Association ◽  
Complex Anatomy ◽  
Wide Range ◽  
Posterior Tympanotomy ◽  
Round Window Niche

Introduction The round window is thought to be an ideal port for inserting electrodes during cochlear implantation. Considering its complex anatomy with an individual variation, this study aims to review the anatomy of round window based on the visibility of round window niche and round window membrane via posterior tympanotomy in pediatric and adult population who underwent cochlear implantation. MethodsThis was a retrospective observational study conducted at the Department of ENT-HNS, Institute of Medicine, Kathmandu, Nepal. Surgical notes of adult (>15 years) and pediatric cases (<15years) who underwent primary cochlear implantation from January 2015 to January 2018 were assessed for different grading of round window niche and round window membrane visibility via posterior tympanotomy. Cases with revision surgery and with incomplete documentation of intra-operative findings were excluded from the study. Statistical analysis was done using SPSS software version 25. We used Chi-square and Fisher’s exact tests to analyze the statistical association. ResultsType B round window niche (partially visible) was the most common variant seen in the pediatric group while in adults, both Type B (partially visible) and Type C (fully visible) round window niche were common. Compared to the adults, the pediatric group had good visibility of RWM. However, there was no statistical association between these observations. ConclusionThe round window has a wide range of anatomical variations with different levels of visibility of RWN and RWM in the different age groups. Although statistically insignificant, RWM visibility seemed to be better in pediatric cases compared to adults.

Mesh Network of eHealth Intelligent Agents for Visually Impaired and Blind People

2022 ◽  
pp. 240-271
Author(s):  
Dmytro Zubov
Keyword(s):  
Intelligent Agents ◽  
Visually Impaired ◽  
Assistive Devices ◽  
Mesh Network ◽  
Assistive Device ◽  
Raspberry Pi ◽  
Industrial Facilities ◽  
Blind And Visually Impaired ◽  
Wide Range ◽  
Human Faces

Smart assistive devices for blind and visually impaired (B&VI) people are of high interest today since wearable IoT hardware became available for a wide range of users. In the first project, the Raspberry Pi 3 B board measures a distance to the nearest obstacle via ultrasonic sensor HC-SR04 and recognizes human faces by Pi camera, OpenCV library, and Adam Geitgey module. Objects are found by Bluetooth devices of classes 1-3 and iBeacons. Intelligent eHealth agents cooperate with one another in a smart city mesh network via MQTT and BLE protocols. In the second project, B&VIs are supported to play golf. Golf flagsticks have sound marking devices with a buzzer, NodeMcu Lua ESP8266 ESP-12 WiFi board, and WiFi remote control. In the third project, an assistive device supports the orientation of B&VIs by measuring the distance to obstacles via Arduino Uno and HC-SR04. The distance is pronounced through headphones. In the fourth project, the soft-/hardware complex uses Raspberry Pi 3 B and Bytereal iBeacon fingerprinting to uniquely identify the B&VI location at industrial facilities.

scholarly journals Daptomycin Dose-Effect Relationship against Resistant Gram-Positive Organisms

2003 ◽  
Vol 47 (5) ◽  
pp. 1598-1603 ◽  
Author(s):  
Raymond Cha ◽  
Richard G. Grucz ◽  
Michael J. Rybak
Keyword(s):  
Bactericidal Activity ◽  
Model Fitting ◽  
Bacterial Density ◽  
Dose Effect ◽  
Pharmacodynamic Modeling ◽  
Gram Positive ◽  
Time Curve ◽  
Initial Inoculum ◽  
Wide Range

ABSTRACT Daptomycin exhibits in vitro bactericidal activity against clinically significant gram-positive bacteria. We employed pharmacodynamic modeling to determine a once-daily dosing regimen of daptomycin that correlates to pharmacodynamic endpoints for different resistant gram-positive clinical strains. An in vitro pharmacodynamic model with an initial inoculum of 6 log10 CFU/ml was used to simulate daptomycin regimens ranging in dose from 0 to 9 mg/kg of body weight/day, with corresponding exposures reflecting free-daptomycin concentrations in serum. Bacterial density was profiled over 48 h for two methicillin-resistant Staphylococcus aureus (MRSA-67 and -R515), two glycopeptide intermediate-resistant S. aureus (GISA-992 and -147398), and two vancomycin-resistant Enterococcus faecium (VREF-12366 and -SF12047) strains. A sigmoid dose-response model was used to estimate the effective dose required to achieve 50% (ED50) and 80% (ED80) bacterial density reduction at 48 h. Daptomycin MICs for study isolates ranged from 0.125 to 4 μg/ml. Model fitting resulted in an r 2 of >0.80 for all tested isolates. Control growths at 48 h ranged from 7.3 to 8.5 log10 CFU/ml. Sigmoid relationships were not superimposable between categorical resistant species: ED50 and ED80 values were 1.9 and 3.1, 4.2 and 5.6, and 5.4 and 6.8 mg/kg for MRSA, GISA, and VREF isolates, respectively. Doses required to achieve ED50 and ED80 values correlated with MIC differences between tested organisms. Corresponding area under the concentration-time curve from 0 to 24 h/MIC exposure ratios demonstrated a wide range of ED80 values among the tested isolates. Doses ranging between 3 and 7 mg/kg produced significant bactericidal activity (ED80) against these multidrug-resistant S. aureus and E. faecium isolates.

scholarly journals Wearable Magnetic Induction-based Approach Toward 3D Motion Tracking

2021 ◽  
Author(s):  
Negar Golestani ◽  
Mahta Moghaddam
Keyword(s):  
Magnetic Induction ◽  
Motion Tracking ◽  
Mean Squared Error ◽  
Average Distance ◽  
Tracking System ◽  
Body Movement ◽  
The Body ◽  
Machine Learning Techniques ◽  
Wide Range ◽  
Battery Capacity

Abstract Activity recognition using wearable sensors has gained popularity due to its wide range of applications, including healthcare, rehabilitation, sports, and senior monitoring. Tracking the body movement in 3D space facilitates behavior recognition in different scenarios. Wearable systems have limited battery capacity, and many critical challenges have to be addressed to gain a trade-off among power consumption, computational complexity, minimizing the effects of environmental interference, and achieving higher tracking accuracy. This work presents a motion tracking system based on magnetic induction (MI) to tackle the challenges and limitations inherent in designing a wireless monitoring system. We integrated a realistic prototype of an MI sensor with machine learning techniques and investigated one-sensor and two-sensor configuration setups for motion reconstruction. This approach is successfully evaluated using measured and synthesized datasets generated by the analytical model of the MI system. The system has an average distance root-mean-squared error (RMSE) error of 3 cm compared to the ground-truth real-world measured data with Kinect.

scholarly journals Validating the automation of different measures of high temperature tolerance of small terrestrial insects

2021 ◽  
Author(s):  
Heidi J. MacLean ◽  
Jonas Hjort Hansen ◽  
Jesper Givskov Sorensen
Keyword(s):  
Thermal Tolerance ◽  
Motion Tracking ◽  
Thermal Adaptation ◽  
Temperature Tolerance ◽  
Temperature Acclimation ◽  
Phenotypic Data ◽  
Automated Method ◽  
Starvation Tolerance ◽  
Wide Range ◽  
Terrestrial Insects

Accurately phenotyping numerous test subjects is essential for most experimental research. Collecting such data can be tedious or time-consuming, and can be biased or limited by manual observations. The thermal tolerance of small ectotherms is a good example of this type of phenotypic data, and it is widely used to investigate thermal adaptation, acclimation capacity and climate change resilience of small ectotherms. Here, we present the results of automatically generated thermal tolerance data using motion tracking on video recordings using two Drosophila species and temperature acclimation to create variation in thermal tolerances and two different heat tolerance assays. We find similar effect sizes of acclimation and hardening responses between manual and automated approaches, but different absolute tolerance estimates. This discrepancy likely reflects both technical differences and the behavioral cessation of movement rather than physiological failure measured in other assays. We conclude that both methods generate biological meaningful results, which reflect different aspects of the thermal biology, find no evidence of inflated variance in the manually scored assays, but find that automation can increase throughput without compromising quality. Further we show that the method can be applied to a wide range of arthropod taxa. We suggest that our automated method is a useful example of through-put phenotyping, and suggest this approach might be applied to other tedious laboratory traits, such as desiccation or starvation tolerance, with similar benefits to through-put. However, the interpretation and potential comparison to results using different methodology rely on thorough validation of the assay and the involved biological mechanism.

Lower Limb Assistive Device Design Optimization Using Musculoskeletal Modeling: A Review

2019 ◽  
Vol 13 (4) ◽  
Author(s):  
Emerson Paul Grabke ◽  
Kei Masani ◽  
Jan Andrysek
Keyword(s):  
Design Optimization ◽  
Lower Limb ◽  
Musculoskeletal Model ◽  
Musculoskeletal Modeling ◽  
Model Complexity ◽  
Clinical Population ◽  
Assistive Device ◽  
Patient Specific ◽  
Device Design ◽  
Musculoskeletal Models

Abstract Many individuals with lower limb amputations or neuromuscular impairments face mobility challenges attributable to suboptimal assistive device design. Forward dynamic modeling and simulation of human walking using conventional biomechanical gait models offer an alternative to intuition-based assistive device design, providing insight into the biomechanics underlying pathological gait. Musculoskeletal models enable better understanding of prosthesis and/or exoskeleton contributions to the human musculoskeletal system, and device and user contributions to both body support and propulsion during gait. This paper reviews current literature that have used forward dynamic simulation of clinical population musculoskeletal models to perform assistive device design optimization using optimal control, optimal tracking, computed muscle control (CMC) and reflex-based control. Musculoskeletal model complexity and assumptions inhibit forward dynamic musculoskeletal modeling in its current state, hindering computational assistive device design optimization. Future recommendations include validating musculoskeletal models and resultant assistive device designs, developing less computationally expensive forward dynamic musculoskeletal modeling methods, and developing more efficient patient-specific musculoskeletal model generation methods to enable personalized assistive device optimization.

An Automatic Transformation Method for the Walking Assistive Device to Walk Between Flat Ground and Stairs Safely

2019 ◽  
Author(s):  
Bo-Rong Yang ◽  
Yu-Cheng Zhang ◽  
Hee-Hyol Lee ◽  
Eiichiro Tanaka
Keyword(s):  
The Elderly ◽  
Transformation Method ◽  
Stair Climbing ◽  
Assistive Device ◽  
Motion Patterns ◽  
Combination Methods ◽  
Target User ◽  
Walking Motion ◽  
Measured Distance ◽  
Huge Challenge

Abstract The main target of this research is to assist the elderly people to walk on different road conditions independently. A method that can transform the walking motion of a walking assistive device between level walking and stair climbing automatically was proposed. To teach the target user how to walk correctly, we defined a trajectory that belongs to healthy people to help the user exercise. Stairs are common in various indoor situations and become a huge challenge for people with gait disorders. To extend the range of physical activity, walking trajectories in different surroundings were imported on the assistive device. Ultrasonic sensors were utilized to detect the distance between stairs and the swing foot. Based on the measured distance, the gait was modified according to a predefined safety distance that was determined experimentally. We also designed trajectory combination methods for changing the device motion patterns between ascending and descending stairs as the walking conditions change. The effectiveness of the system was tested through simulation. The results showed that the device smoothly shifted gait with the proposed methods in this paper. This method has the potential to solve the adaptability of various walking devices to different surroundings.

scholarly journals Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5104 ◽  
Author(s):  
Justin Amadeus Albert ◽  
Victor Owolabi ◽  
Arnd Gebel ◽  
Clemens Markus Brahms ◽  
Urs Granacher ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Gold Standard ◽  
Motion Tracking ◽  
Tracking Performance ◽  
Time Step ◽  
Kinect V2 ◽  
Pose Tracking ◽  
Kinect Camera ◽  
Gait Parameters ◽  
Wide Range

Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.

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