Motion Analysis Method Research Articles

The HAN method for a thermal analysis of forced non-Newtonian MHD Reiner-Rivlin viscoelastic fluid motion between two disks

In this article, the semi-analytical technique of the Hybrid Analytical and Numerical Method (the HAN Method) is used to study the non-transient forced non-Newtonian MHD Reiner-Rivlin viscoelastic fluid motion that is constrained between two plates. The magnetic field is also present in this model. The governing equations are in the PDE form and by using the Von Kármán similarity variables, they transformed into a set of ODEs. The HAN-method is applied to solve the ODEs and their associated boundary conditions, analytically. In addition, for the validation, the HAN solution results were compared with the HPM and numerical technique of Runge-Kutta results. And finally, new results were extracted from the HAN solutions in a quantitative form.

Human motion analysis and measurement techniques: current application and developing trend

Human motion analysis and measurement technology have been widely used in the fields of medical treatment, sports science, and rehabilitation. In clinical practice, motion analysis has been applied in the diagnosis and individualized treatment planning of various musculoskeletal diseases, and it is also an important objective scientific method to evaluate the therapeutic effect and the effectiveness of medical equipment. This study aimed to introduce the common modern motion capture measurement technology and equipment, the clinical application and limitations of motion analysis, and the possible development trend of motion analysis measuring techniques in the future. Motion analysis and measurement systems and medical image measurement and analysis technology have made landmark improvements over the past few decades in terms of orthopaedical biomechanics. Nevertheless, limitations still exist, both subjective and objective. All these drawbacks have promoted the exploration of the integrated methods that have now been widely used in motion analysis. The results of the case study about the subject-specific finite element modeling of the foot and sports shoe complex have also shown great consistency. Nevertheless, several possible future directions for motion analysis measuring techniques still exist. In the future, the progress of motion analysis and measurement methods will simultaneously drive the progress of orthopedics, rehabilitation, precision personalized medicine, and medical engineering.

An Inertial-Based Upper-Limb Motion Assessment Model: Performance Validation Across Various Motion Tasks

Inertial measurement unit (IMU) has been widely applied in the development of upper-limb motion assessment model due to its portability, low cost, and theoretically unlimited workspace. However, most inertial-based models do not meet the accuracy requirement of clinical use. The errors mainly arise from the sensor measurement and “sensor-to-segment” misalignment. This article presented a novel inertial-based upper-limb motion assessment model with two layers, which enabled simultaneous estimation of the joint angles and positions. The sensor-to-segment dynamic calibration method was employed in the construction of the upper-limb kinematic model. The joint angles were calculated based on orientation transforms between adjacent body segments, while the joint positions were estimated using a forward kinematic chain. The model performance was evaluated with the terms of the Pearson correlation coefficient (PCC), offset, and root-mean-square error (RMSE) by comparing with results derived from the Vicon reference system. Effects of motion type and motion plane on estimation accuracy were further investigated with the use of a two-way analysis of variance (ANOVA). The results showed that the estimated joint angles and positions had a good agreement with the reference, and the RMSEs below 5.79° and 3.45 cm were, respectively, achieved. Both the motion type and motion plane had significant effects on the model performance, suggesting that the motion task effect should be considered in applications of inertial-based motion analysis methods. The proposed inertial model has great potential in upper-limb movement evaluation for patients.

Technique analyses of the trunk stability for freestyle swimming athlete: case report of an elite athlete

<p>目的：在競技游泳戰國時代，各游泳強國使用先進科學方法優化訓練。然而，在傳統訓練和缺乏科技環境以模擬真實條件下，導致國內選手對於技術的改善效果受到限制。為找出更精準的動作分析和監測方法，本研究目的是藉由角速度感測器監測游泳選手動作，以作為選手動作穩定性的技術改善。方法：本研究以台灣一位自由式奧運級選手為對象，採用慣性測量單元進行選手身上六個感測點的資料數據收集。在 50 公尺自由式的游泳中，選手動作透角速度感測器測量，獲得資訊並回饋給教練，分析後執行新的穩定性矯正訓練計畫。經過 12 週訓練，讓選手再回到測驗現場測驗，經數據比對前、後測驗的角速度差異以評估改善成效。結果：由角速度結果的判讀，可知選手的 X 軸與 Y 軸經過校正訓練後都較前測穩定，減少 X 軸旋轉的不對稱及 Y 軸的上下晃動 (Y 軸最大改善 60 %)。但是，感測器的結果也顯示，因為矯正訓練，導致 Z 軸發生代償現象，造成後測的左右晃動較前測大 (Z 軸增加 70 %)。結論：本研究顯示受試者脊椎的感測器，有助於分析選手於各三個方向軸線動作的細微變化，介入矯正訓練後，能改善受試者於游泳各階段動作的穩定性，同時感測器的輔助也發現代償的現象，將更有助於未來教練的訓練和調整方向。</p> <p> </p><p>Purpose: In competitive swimming, teams try their best to use advanced scientific methods to optimize training. However, traditional training lacks the technological environment to simulate the real conditions. Therefore, the improvement of the athletes’ swimming technique is limited. To find out a more accurate movement analysis and technical monitoring method, this study uses the angular velocity sensor to determine the different points of the athletes’ movements during swimming through the sensor device, to improve the stability of the athletes’ movements. Methods: This study took freestyle Olympians as the subjects. The inertial measurement unit was used to collect data on six detection points on the athletes’ bodies, and to analyze the processes of catching water, pushing water, moving arms in the air, and returning to the water. In the 50-meter freestyle swimming, the athletes’ movements were measured through the angular velocity sensor, and the data were collected and fed back to the coach to implement a new training plan. After 12 weeks of corrective training, the athlete returned to the test. The differences in angular velocity between the pre-test and the post-test were compared. Results: Our analysis indicates that, after corrective training, the athletes’ post-test X-axial and Y-axial data are more stable than those from the pre-test which reduces the asymmetry of the X-axis rotation and the up and down shaking of the Y-axis (improving Y-axis 60 %). However, the sensor data results also show that the Z-axial rotation is compensated due to the corrective training, causing the left and right shaking of the post-test to be larger than that of the pre-test (Z-axial 70 % worse). Conclusion: This method proves that the sensor can record information on the athletes’ movements, and then analyze the stability of the athletes’ movements in each stage of swimming. The results also show that the sensors attached to the athletes’ back were helpful to distinguish the subtle changes in the athletes’ movements in each of the three axes. These results could also be of great assistance for coaches to improve their athletes’ postures and future training direction.</p> <p> </p>

Array invariant-based range-only target motion analysis for ship noise measured by two vertical line arrays in shallow water

A novel approach for underwater acoustic localization by using passive line array sonar will be proposed in this talk. In the case of the received signal having a finite pulse duration, the target location can be easily estimated using the time-difference-of-arrival (TDOA) method between sensors. However, it is difficult to use the TDOA method for signals that exist for a relatively long time, such as ship noise. An array invariant method has been proposed to measure the source-receiver distance, but it does not accurately estimate the target location. In this talk, target localization will be performed with the range-only target motion analysis method using non-linear target tracking after estimating the target range by the array invariant method. The proposed method is tested using the ship noise of the R/V Onnuri measured by two vertical line arrays during the Shallow-water Acoustic Variability Experiment (SAVEX-15), and the result will be discussed in this talk. [This research was supported by the Ministry of Oceans and Fisheries of Korea (PM63010, 2022).]

Effect of Perspective on Eye Movement of Aesthetic Preference Research on Wai Shape of New Chinese Style Arhat Bed

The new chinese style Arhat bed is taken as the research objective to explore the effect of people’s view on people’s aesthetic preferences for Wai shape of new chinese Arhat bed, using the eye movement analysis method through comprehensive analysis on eye movement data from volunteers. Eye movements characteristics of 20 volunteers in watching pictures of different new chinese Arhat bed Wai shape are recorded by SR research Eyelink head mounted eye tracker. Experimental results show that eye movement data of men and women are in the same trend, but there are few data in instability and the male and female have a significant correlation with the time and the number of fixation points, with a obvious regression effect, under two different presented Perspective of products. In all 16 samples selected, samples 12 has the most fixation and fixation times, while samples 15 and samples 13 has the least. Visual fatigue and the difference between 3D model and the real Arhat bed products have some effects on the experimental data. It makes no difference for people to choose products from different perspectives in where the products are placed, and people prefer the Wai shape which contains column and is simple.

Pre-braking behaviors analysis based on Hilbert–Huang transform

Previous studies have shown that about 90% of traffic accidents are due to human error, which means that human factors may affect a driver's braking behaviors and thus their driving safety, especially when the driver makes a braking motion. However, most studies have mounted sensors on the brake pad, ignoring to some extent an analysis of the driver's behavior before the brake pad is pressed (pre-braking). Therefore, to determine the effect of different human factors on drivers' pre-braking behaviors, this study focused on analyzing drivers' local joints (knee, ankle, and toe) by a motion capture device. A Hilbert–Huang Transform (HHT)-based local human body movement analysis method was used to decompose the realistic complex pre-braking actions into sub-actions such as intrinsic mode functions (IMF1, IMF2, etc.). Analysis of the results showed that IMF1 is a common and necessary action when pre-braking for all drivers, and IMF2 may be the safety assurance action that allows right-foot transverse movement at the beginning part of the pre-braking process. We also found that the experienced, male, and Phys.50 groups may have consistent characteristics in the HHT scheme, which could mean that such drivers would have better performance and efficiency during the pre-braking process. The results of this study will be useful in decomposing and discerning the specific actions that lead to accidents, providing insights into driver training for novice drivers, and guiding the construction of daily automated driver assistance or accident prevention systems (advanced driver assistance systems, ADASs).

A novel gait analysis system for detecting abnormal hemiparetic gait patterns during robot-assisted gait training: A criterion validity study among healthy adults.

Robot-assisted gait training has been reported to improve gait in individuals with hemiparetic stroke. Ideally, the gait training program should be customized based on individuals' gait characteristics and longitudinal changes. However, a gait robot that uses gait characteristics to provide individually tailored gait training has not been proposed. The new gait training robot, "Welwalk WW-2000," permits modification of various parameters, such as time and load of mechanical assistance for a patient's paralyzed leg. The robot is equipped with sensors and a markerless motion capture system to detect abnormal hemiparetic gait patterns during robot-assisted gait training. Thus, it can provide individually tailored gait training. This study aimed to investigate the criterion validity of the gait analysis system in the Welwalk WW-2000 in healthy adults. Twelve healthy participants simulated nine abnormal gait patterns that were often manifested in individuals with hemiparetic stroke while wearing the robot. Each participant was instructed to perform a total of 36 gait trials, with four levels of severity for each abnormal gait pattern. Fifteen strides for each gait trial were recorded using the markerless motion capture system in the Welwalk WW-2000 and a marker-based three-dimensional (3D) motion analysis system. The abnormal gait pattern index was then calculated for each stride from both systems. The correlation of the index values between the two methods was evaluated using Spearman's rank correlation coefficients for each gait pattern in each participant. Using the participants' index values for each abnormal gait pattern obtained using the two motion analysis methods, the median Spearman's rank correlation coefficients ranged from 0.68 to 0.93, which corresponded to moderate to very high correlation. The gait analysis system in the Welwalk WW-2000 for real-time detection of abnormal gait patterns during robot-assisted gait training was suggested to be a valid method for assessing gait characteristics in individuals with hemiparetic stroke. [https://jrct.niph.go.jp], identifier [jRCT 042190109].

Stability analysis of planetary systems via second-order Rényi entropy

ABSTRACT The long-term dynamical evolution is a crucial point in recent planetary research. Although the amount of observational data are continuously growing and the precision allows us to obtain accurate planetary orbits, the canonical stability analysis still requires N-body simulations and phase space trajectory investigations. We propose a method for stability analysis of planetary motion based on the generalized Rényi entropy obtained from a scalar measurement. The radial velocity data of the central body in the gravitational three-body problem are used as the basis of a phase space reconstruction procedure. Then, Poincaré’s recurrence theorem contributes to finding a natural partitioning in the reconstructed phase space to obtain the Rényi entropy. It turns out that the entropy-based stability analysis is in good agreement with other chaos detection methods, and it requires only a few tens of thousands of orbital period integration time.

Research on Classroom Emotion Recognition Algorithm Based on Visual Emotion Classification.

In this paper, we construct a classroom emotion recognition algorithm by classifying visual emotions for improving the quality of classroom teaching. We assign weights to the training images through an attention mechanism network and then add a designed loss function so that it can focus on the feature parts of face images that are not obscured and can characterize the target emotion, thus improving the accuracy of facial emotion recognition under obscuration. Analyze the salient expression features of classroom students and establish a classification criteria and criteria library. The videos of classroom students' facial expressions are collected, a multi-task convolutional neural network (MTCNN) is used for face detection and image segmentation, and the ones with better feature morphology are selected to build a standard database. A visual motion analysis method with the fusion of overall and local features of the image is proposed. To validate the effectiveness of the designed MTCNN model, two mainstream classification networks, VGG16 and ResNet18, were tested and compared with MTCNN by training on RAF-DB, masked dataset, and the classroom dataset constructed in this paper, and the final accuracy after training was 78.26% and 75.03% for ResNet18 and VGG16, respectively. The results show that the MTCNN proposed in this paper has a better recognition effect. The test results of the loss function also show that it can effectively improve the recognition accuracy, and the MTCNN model has an accuracy of 93.53% for recognizing students' facial emotions. Finally, the dataset is extended with the training method of expression features, and the experimental study shows that the method performs well and can carry out recognition effectively.

Analytical Model of Hole Diameter and Self-Guiding Machining Mechanism of BTA Deep Hole Drilling

The goal of this study was to explore the self-guided machining mechanism of boring and trepanning association (BTA) deep hole drilling and realize precise control of the machining quality. The motion analysis method was used to analyze the center motion trajectory of the drill during the entrance, and the self-guiding mechanism and hole-forming mechanism of BTA deep hole drilling were revealed. Considering the bending deformation of the drilling tube and the tool structure parameters, according to the elastic-plastic deformation theory and Hertzian contact theory, a novel analytical model of the extrusion contact between the guide pads and the hole wall of the BTA deep hole drilling was established for the theoretical prediction of the extrusion deformation and the machining hole diameter. Combined with the finite element method (FEM) simulation model, the variation law of the contact inclination angle, contact stress, and extrusion deformation of the guide pads and the hole wall with the drilling conditions were studied. The total extrusion deformation between the guide pad and the hole wall was between 10 and 50 μm. The maximum error between the FEM simulation results and the test results was 18.1%, and the maximum error between the analytical model results and the test results was 23.6%. The simulation and experimental results showed that the established extrusion contact model could accurately predict the extrusion deformation of the hole wall and the machining hole diameter.

MoveApps: a serverless no-code analysis platform for animal tracking data

BackgroundBio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills.ResultsWe developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface.Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository.The platform was beta launched in spring 2021 and currently contains 49 Apps that are used by 316 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements.ConclusionsThe MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.

Scene Construction and Application of Panoramic Virtual Simulation in Interactive Dance Teaching Based on Artificial Intelligence Technology

In recent years, with the rapid development of human motion simulation technology and virtual simulation technology, natural human-computer interaction has become the main form of research in the computer industry. Due to the research capabilities and practical value of mobile video technology, it is widely used in advanced fields, such as video animation production, rehabilitation medicine, sports training, and game software, effectively realizing the connection between the three-dimensional world and the simulation world. However, the application of motion imaging technology in teaching activities is not perfect. This article is based on dance teaching, adopts a dance movement analysis method based on vector matching, and uses artificial intelligence technology to create a virtual panoramic scene. Experimental data show that the average recognition rate of gestures is 89.8%, which can meet the gesture switching interaction of working conditions in virtual simulation of equipment operation.

Software for non-parametric image registration of 2-photon imaging data.

Functional 2-photon microscopy is a key technology for imaging neuronal activity. The recorded image sequences, however, can contain non-rigid movement artifacts which requires high-accuracy movement correction. Variational optical flow (OF) estimation is a group of methods for motion analysis with established performance in many computer vision areas. However, it has yet to be adapted to the statistics of 2-photon neuroimaging data. In this work, we present the motion compensation method Flow-Registration that outperforms previous alignment tools and allows to align and reconstruct even low signal-to-noise ratio 2-photon imaging data and is able to compensate high-divergence displacements during local drug injections. The method is based on statistics of such data and integrates previous advances in variational OF estimation. Our method is available as an easy-to-use ImageJ/FIJI plugin as well as a MATLAB toolbox with modular, object oriented file IO, native multi-channel support and compatibility with existing 2-photon imaging suites.

Regional diaphragm motion analysis via dynamic MRI.

Breathing-related movement analysis is important in the study of many disease processes. The analysis of diaphragmatic motion via thoracic imaging in particular is important in a variety of disorders. Compared to computed tomography (CT) and fluoroscopy, dynamic magnetic resonance imaging (dMRI) has several advantages, such as better soft tissue contrast, no ionizing radiation, and greater flexibility in selecting scanning planes. In this paper, we propose a novel method for full diaphragmatic motion analysis via free-breathing dMRI. Firstly, after 4D dMRI image construction in a cohort of 51 normal children, we manually delineated the diaphragm on sagittal plane dMRI images at end-inspiration and end-expiration. Then, 25 points were selected uniformly and homologously on each hemi-diaphragm surface. Based on the inferior-superior displacements of these 25 points between end-expiration (EE) and end-inspiration (EI) time points, we obtained their velocities. We then summarized 13 parameters from these velocities for each hemi-diaphragm to provide a quantitative regional analysis of diaphragmatic motion. We observed that the regional velocities of the right hemi-diaphragm were almost always statistically significantly greater than those of the left hemi-diaphragm in homologous locations. There was a significant difference for sagittal curvatures but not for coronal curvatures between the two hemi-diaphragms. Using this methodology, future larger scale prospective studies may be considered to confirm our findings in the normal state and to quantitatively assess regional diaphragmatic dysfunction when various disease conditions are present.

Motion Action Analysis at Basketball Sports Scene Based on Image Processing

To solve the problems of low accuracy and high time cost in manual recording and statistics of basketball data, an automatic analysis method of motion action under the basketball sports scene based on the spatial temporal graph convolutional neural network is proposed. By using the graph structure in the data structure to model the joints and limbs of the human body, and using the spatial temporal graph structure to model the posture action, the extraction and estimation of human body posture in basketball sports scenes are realized. Then, training combined with transfer learning, the recognition of motion fuzzy posture is realized through the classification and application of a label subset. Finally, using the self-made OpenCV to collect and calibrate NBA basketball videos, the effectiveness of the proposed method is verified by analyzing the motion action. The results show that the proposed method based on the spatial temporal graph convolutional neural network can recognize all kinds of movements in different basketball scenes. The average recognition accuracy is more than 75%. It can be seen that the method has certain practical application value. Compared with the common motion analysis method feature descriptors, the motion action analysis method based on the spatial temporal graph convolution neural network has higher identification accuracy and can be used for motion action analysis in the actual basketball sports scenes.

Small Random Angular Variations in Pelvic Tilt and Lower Extremity Can Cause Error in Static Image-based Preoperative Hip Arthroplasty Planning: A Computer Modeling Study.

Many THA simulation models rely on a limited set of preoperative static radiographs to replicate sagittal pelvic tilt during functional positions and to recommend an implant orientation that minimizes the risk of prosthetic impingement. However, possible random changes in pelvic or lower extremity angular motions and the effect of coronal and axial pelvic tilt are not included in these preoperative models. (1) Can prosthetic impingement occur if the pelvic tilt or lower extremity alignment randomly varies up to ± 5° from what is measured on a single preoperative static radiographic image? (2) Do changes in coronal and axial pelvic tilt or lower extremity alignment angles have a similar effect on the risk of prosthetic impingement? A de-identified pelvis and lower-body CT image of a male patient without previous THA or lower extremity surgery was used to import the pelvis, femur, and tibia into a verified MATLAB computer model. The motions of standing, pivoting, sitting, sit-to-stand, squatting, and bending forward were simulated. THA implant components included a full hemispherical acetabular cup without an elevated rim, polyethylene liner without an elevated rim, femoral head (diameter: 28 mm, 32 mm, 36 mm, or 40 mm), and a triple-taper cementless stem with three different neck shaft angles (127°, 132°, or 135°) with a trapezoidal neck were used in this model. A static model (cup anatomical abduction 40°, cup anatomical anteversion 20°, stem anatomical anteversion 10°) with a predefined range of sagittal pelvic tilt and hip alignment (0° coronal or axial tilt, without random ± 5° change) was used to simulate each motion. We then randomly varied pelvic tilt in three different pelvic planes and hip alignments (flexion, extension, abduction, adduction, rotation) up to ± 5° and assessed the same motions without changing the implant's anatomical orientation. Prosthetic impingement as the endpoint was defined as mechanical abutment between the prosthetic neck and polyethylene liner. Multiple logistic regression was used to investigate the effect of variation in pelvic tilt and hip alignment (predictors) on prosthetic impingement (primary outcome). The static-based model without the random variation did not result in any prosthetic impingement under any conditions. However, with up to ± 5° of random variation in the pelvic tilt and hip alignment angles, prosthetic impingement occurred in pivoting (18 possible combinations), sit-to-stand (106 possible combinations), and squatting (one possible combination) when a 28-mm or a 32-mm head was used. Variation in sagittal tilt (odds ratio 4.09 [95% CI 3.11 to 5.37]; p < 0.001), axial tilt (OR 3.87 [95% CI 2.96 to 5.07]; p < 0.001), and coronal tilt (OR 2.39 [95% CI 2.03 to 2.83]; p < 0.001) affected the risk of prosthetic impingement. Variation in hip flexion had a strong impact on the risk of prosthetic impingement (OR 4.11 [95% CI 3.38 to 4.99]; p < 0.001). The combined effect of 2° to 3° of change in multiple pelvic tilt or hip alignment angles relative to what is measured on a single static radiographic image can result in prosthetic impingement. Relying on a few preoperative static radiographic images to minimize the risk of prosthetic impingement, without including femoral implant orientation, axial and coronal pelvic tilt, and random angular variation in pelvis and lower extremity alignment, may not be adequate and may fail to predict prosthetic impingement-free ROM. Determining a safe zone for THA implant positioning with respect to impingement may require a dynamic computer simulation model to fully capture the range of possible impingement conditions. Future work should concentrate on devising simple and easily available methods for dynamic motion analysis instead of using a few static radiographs for preoperative planning.

An advanced method of individual jaw movement analysis

An advanced method of individual jaw movement analysis

Research on Analysis Method of Shock Absorption Behavior of Cellular Solid in Volumetric Contact

This study proposes a numerical analysis model that considers volumetric contact in cellular solid such as metal foam. Volumetric contact refers to contact with uneven or curved surfaces. The proposed analytical model is based on a motion analysis method of multibody system with contact and yield using linear complementarity problem. The current analytical method assumes surface contact. In order to consider volumetric contact, a discrete analytical model is proposed. In addition, the tearing phenomenon of cells observed in indentation tests is used to express the yield force by introducing tearing energy in addition to the stress required for compression. Numerical analysis was performed on the proposed analytical model. Numerical analysis was performed assuming the case of carbon steel crashing on a portion of aluminum foam so that deformation occurs in the unevenness. The volumetric contact is evaluated from the analysis results of time history of plastic strain and contact force.

Motion Sensitivity Analysis of Multibody Systems by Null Space Matrix Method of Differential Equation Type

One of the authors has proposed a motion analysis method for multibody systems called nullspace matrix method of differential equation type. In the proposed method, a nullspace matrix for the constraint Jacobian matrix is obtained by solving a differential equation. Then, the term which represents the constraint force in the equation of motion is eliminated with the nullspace matrix. The proposed method is applicable to systems with singular configurations. For efficient design of machines and structures, sensitivity of the behavior of the system with respect to design variables such as lengths of linkages and positions of joints is required. In this research, based on the procedure of the nullspace matrix method of differential equation type, a motion sensitivity analysis method of multibody systems is proposed. An example of motion sensitivity is presented.