scholarly journals Kinematic gait characteristics of straight line walk in clinically sound dairy cows

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253479
Author(s):  
M. Tijssen ◽  
F. M. Serra Braganςa ◽  
K. Ask ◽  
M. Rhodin ◽  
P. H. Andersen ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Linear Mixed Model ◽  
Vertical Displacement ◽  
Video Data ◽  
Lower Limbs ◽  
Anatomical Location ◽  
Distal Limb ◽  
Temporal Parameters ◽  
Gait Characteristics ◽  
Straight Line

The aim of this study is to describe the kinematic gait characteristics of straight line walk in clinically sound dairy cows using body mounted Inertial Measurement Units (IMUs) at multiple anatomical locations. The temporal parameters used are speed and non-speed normalized stance duration, bipedal and tripedal support durations, maximal protraction and retraction angles of the distal limbs and vertical displacement curves of the upper body. Gait analysis was performed by letting 17 dairy cows walk in a straight line at their own chosen pace while equipped with IMU sensors on tubera sacrale, left and right tuber coxae (LTC and RTC), back, withers, head, neck and all four lower limbs. Data intervals with stride by stride regularity were selected based on video data. For temporal parameters, the median was calculated and 95% confidence intervals (CI) were estimated based on linear mixed model (LMM) analysis, while for limb and vertical displacement curves, the median and most typical curves were calculated. The temporal parameters and distal limb angles showed consistent results with low variance and LMM analysis showed non-overlapping CI for all temporal parameters. The distal limb angle curves showed a larger and steeper retraction angle range for the distal front limbs compared with the hind limbs. The vertical displacement curves of the sacrum, withers, LTC and RTC showed a consistent sinusoidal pattern while the head, back and collar curves were less consistent and showed more variation between and within cows. This kinematic description might allow to objectively differentiate between normal and lame gait in the future and determine the best anatomical location for sensor attachment for lameness detection purposes.

scholarly journals Influence of BMI on Gait Characteristics of Young Adults: 3D Evaluation Using Inertial Sensors

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4221 ◽  
Author(s):  
Valeria Rosso ◽  
Valentina Agostini ◽  
Ryo Takeda ◽  
Shigeru Tadano ◽  
Laura Gastaldi
Keyword(s):  
Young Adults ◽  
Inertial Sensors ◽  
Joint Kinematics ◽  
Normal Weight ◽  
Lower Limbs ◽  
Opening Angle ◽  
Temporal Parameters ◽  
Gait Characteristics ◽  
Spatio Temporal ◽  
Soft Tissue Artifact

Overweight/obesity is a physical condition that affects daily activities, including walking. The main purpose of this study was to identify if there is a relationship between body mass index (BMI) and gait characteristics in young adults. 12 normal weight (NW) and 10 overweight/obese (OW) individuals walked at a self-selected speed along a 14 m indoor path. H-Gait system, combining seven inertial sensors (fixed on pelvis and lower limbs), was used to record gait data. Walking speed, spatio-temporal parameters and joint kinematics in 3D were analyzed. Differences between NW and OW and correlations between BMI and gait parameters were evaluated. Conventional spatio-temporal parameters did not show statistical differences between the two groups or correlations with the BMI. However, significant results were pointed out for the joint kinematics. OW showed greater hip joint angles in frontal and transverse planes, with respect to NW. In the transverse plane, OW showed a greater knee opening angle and a shorter length of knee and ankle trajectories. Correlations were found between BMI and kinematic parameters in the frontal and transverse planes. Despite some phenomena such as soft tissue artifact and kinematics cross-talk, which have to be more deeply assessed, current results show a relationship between BMI and gait characteristics in young adults that should be looked at in osteoarthritis prevention.

scholarly journals Changes in Dairy Cow Behavior with and without Assistance at Calving

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 722
Author(s):  
Bethan Cavendish ◽  
John McDonagh ◽  
Georgios Tzimiropoulos ◽  
Kimberley R. Slinger ◽  
Zoë J. Huggett ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Video Surveillance ◽  
Dairy Cow ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Behavioral Data ◽  
Behavioral Patterns ◽  
Holstein Friesian ◽  
Time Periods

The aim of this study was to characterize calving behavior of dairy cows and to compare the duration and frequency of behaviors for assisted and unassisted dairy cows at calving. Behavioral data from nine hours prior to calving were collected for 35 Holstein-Friesian dairy cows. Cows were continuously monitored under 24 h video surveillance. The behaviors of standing, lying, walking, shuffle, eating, drinking and contractions were recorded for each cow until birth. A generalized linear mixed model was used to assess differences in the duration and frequency of behaviors prior to calving for assisted and unassisted cows. The nine hours prior to calving was assessed in three-hour time periods. The study found that the cows spent a large proportion of their time either lying (0.49) or standing (0.35), with a higher frequency of standing (0.36) and shuffle (0.26) bouts than other behaviors during the study. There were no differences in behavior between assisted and unassisted cows. During the three-hours prior to calving, the duration and bouts of lying, including contractions, were higher than during other time periods. While changes in behavior failed to identify an association with calving assistance, the monitoring of behavioral patterns could be used as an alert to the progress of parturition.

Estimating meal criteria for meal pattern analysis of dairy cows

1999 ◽  
Vol 1999 ◽  
pp. 203-203
Author(s):  
B J Tolkamp ◽  
D J Allcroft ◽  
I Kyriazakis
Keyword(s):  
Dairy Cows ◽  
Frequency Distribution ◽  
Pattern Analysis ◽  
Interval Length ◽  
Implicit Assumption ◽  
Short Intervals ◽  
Meal Pattern ◽  
Straight Line ◽  
Negative Exponential ◽  
Frequency Curves

Meal pattern analyses depend crucially on appropriate estimates of bout or meal criteria (i.e., the longest non-feeding intervals accepted as part of a meal). Bout criteria are frequently estimated after fitting a ‘broken-stick’ to the un-transformed, the log-transformed, or the log-transformed cumulative (log-survivorship), frequency distribution of between-feeding interval length. We know of no biological justification for fitting a broken stick to the frequency distribution of short intervals between feeding events and can, therefore, not interpret ‘criteria’ obtained that way. The methods that fit a broken-stick to log-survivorship or log-frequency curves are based on the implicit assumption that the probability of an animal initiating a bout is independent of the time since the last bout. Only then will the length of intervals between bouts be distributed as a negative exponential that appears as a straight line after log-transformation. However, the satiety concept predicts that this probability is not constant but increases with time since the last meal.

A Design of the Device for Lower Limbs Rehabilitation and Simulation Analysis

2011 ◽  
Vol 130-134 ◽  
pp. 438-441
Author(s):  
Yong Wang ◽  
Ying Zhang ◽  
Ji Fen Li
Keyword(s):  
Electric Motor ◽  
Simulation Analysis ◽  
Vertical Displacement ◽  
The Other ◽  
Lower Limbs ◽  
Two Dimensional ◽  
Adams Software ◽  
Four Bar Linkage ◽  
Rehabilitation Exercise

Based on the positional characteristic of ellipticorbit of four-bar linkage, we develop a device to support rehabilitation of a patient’s lower limb’s motion in two-dimensional plane. In addition, we use ADAMS software to analyze two aspects parameters. One aspect is about the horizontal and vertical displacement of four-bar mechanism of ellipticorbit. The other simulation is about angles θ1 (angle between thigh and the horizontal) and θ2 (angle between thigh and calf). Before using the device, we install them in both sides of a normal chair. Driven by electric motor, lower limbs can follow the trajectory to do rehabilitation exercise. Long-term exercise can help a patient to repair damaged muscles.

scholarly journals A Deep Neural Network for Gait Classification Based on Inertial Sensors in Post-Stroke Patients

2020 ◽  
Author(s):  
Fu-Cheng Wang ◽  
Chin-Hsien Lin ◽  
Wei Yuan ◽  
You-Chi Li ◽  
Tien-Yun Kuo ◽  
...  
Keyword(s):  
Neural Network ◽  
Motion Capture ◽  
Deep Neural Network ◽  
Time Window ◽  
Lower Limbs ◽  
Motion Capture System ◽  
Data Set ◽  
Gait Characteristics ◽  
Physical Activity Monitoring ◽  
Average Accuracy

Abstract Background: Stroke survivors usually experience partial disability, due to abnormal gaits, which vary widely and require tailored rehabilitation programs. However, most gait classifications are based mainly on clinical assessments, which can be influenced by the therapist’s experience. Inertial measurement units (IMUs) are devices that combine accelerometers and gyroscopes to detect movement. IMUs have been successfully used for assessing gait characteristics. Here, we aimed to develop a Deep Neural Network (DNN) model that incorporated information from a motion capture system and multi-labeling IMUs information. This DNN was developed to recognize individual gait patterns in patients affected by stroke to facilitate the design of suitable rehabilitation strategies and promote functional recovery.Methods: We recruited ten patients, aged 20–75 years, with a first-ever, unilateral, ischemic stroke, which caused mild to moderate leg paresis 4 weeks after stroke and ten neurologically normal healthy controls. We applied a motion capture system integrated with multi-label IMUs to acquire the gait information. The motion capture system measured gait information by detecting movement of LED markers attached to each participant. In addition, the IMUs were attached to each participant’s lower limbs to measure kinematic data. These measurements were then applied to the development of a DNN model that could recognize gait characteristics in patients after a stroke and in normal controls.Results: The DNN model achieved an average accuracy of 98.28% in differentiating the stroke gait from the normal gait. Among patients with stroke, the DNN model had an average accuracy of 96.86% in classifying the gait abnormality as either a drop-foot gait or a circumduction gait. We also applied a publicly available dataset, the Physical Activity Monitoring Data Set, which contained IMU information from another independent set of participants to validate our DNN model. We found an average accuracy of 98.60%.Conclusions: We developed a DNN model based on integrated information from a motion capture system and multi-label IMU inputs. This model might assist clinicians and therapists in identifying abnormal gaits more accurately and in applying suitable training programs within the “golden time window” of rehabilitation, after the onset of stroke.

Can post-milking insemination increase conception rate in high-producing Holstein cows under heat stress? A retrospective study

2019 ◽  
Vol 157 (03) ◽  
pp. 254-259
Author(s):  
R. Rahbar ◽  
A. Sadeghi-Sefidmazgi ◽  
R. Abdullahpour ◽  
A. Nejati-Javaremi
Keyword(s):  
Heat Stress ◽  
Dairy Cows ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Management Strategies ◽  
High Heat ◽  
Conception Rate ◽  
Low Fertility ◽  
Significant Interaction Effect ◽  
Dairy Animals

AbstractHeat stress, especially in countries with hot climates, is a major cause of low fertility in high-producing dairy herds. Management strategies are needed to help producers improve the reproductive performance of their dairy animals under such conditions. The current study aims to evaluate the effects of pre- and post-milking insemination on the conception rate (CR) in dairy cows. The dataset included 1294 insemination records leading to pregnancy in 708 lactating Holstein dairy cows. The GLIMMIX model procedure of SAS based on the generalized linear mixed model methodology was used to analyse the results of insemination (success or failure) as a binomial distribution with the logit link function. Differences were observed in CRs between pre- and post-milking insemination. The pregnancy odds ratio (OR) for post-milking insemination relative to that for pre-milking one was estimated at 1.90 [1.23‒2.91; 95% confidence interval (CI)]. Different levels of interaction were obtained between average daily milk production and time of insemination. In the high-producing group, the pregnancy OR for the post-milking relative to that for the pre-milking insemination was estimated at 3.53 (2.00‒6.24; 95% CI). A significant interaction effect was obtained between insemination time and the temperature-humidity index. A pregnancy OR of 2.52 (1.22‒4.14; 95% CI) was recorded for the cows inseminated after milking on days with higher levels of heat and humidity stress v. the pre-milking inseminated ones. Based on the results, post-milking insemination of high-producing cows increased CRs, especially on days with high heat and humidity stress.

Quantitative body symmetry assessment during neurological examination

2020 ◽  
Vol 28 (5) ◽  
pp. 573-584
Author(s):  
Kristina Daunoraviciene ◽  
Jurgita Ziziene ◽  
Agne Ovcinikova ◽  
Rasa Kizlaitiene ◽  
Julius Griskevicius
Keyword(s):  
Inertial Sensors ◽  
The Body ◽  
Lower Limbs ◽  
Upper Body ◽  
Lower Body ◽  
Temporal Parameters ◽  
Body Asymmetry ◽  
Upper And Lower Extremities ◽  
Spatiotemporal Parameters ◽  
Measurement Units

BACKGROUND: A lack of movement coordination characterized by the undershoot or overshoot of the intended location with the hand, arm, or leg is often found in individuals with multiple sclerosis (MS). Standardized as Finger-to-Nose (FNT) and The Heel-to-Shin (HST) tests are the most frequently used tests for qualitative examination of upper and lower body coordination. Inertial sensors facilitate in performing quantitative motion analysis and by estimating body symmetry more accurately assess coordination lesion and imbalance. OBJECTIVES: To assess the body symmetry of upper and lower limbs quantitatively, and to find the best body symmetry indices to discriminate MS from healthy individuals (CO). METHODS: 28 MS patients and 23 CO participated in the study. Spatiotemporal parameters obtained from six Inertial Measurement Units (IMUs) were placed on the upper and lower extremities during FNT and HST tests. All data were analyzed using statistical methods in MATLAB. RESULTS: Asymmetry indices of temporal parameters showed a significant increase in upper body and lower body asymmetry of MS compared to CO. However, CO have a greater kinematic asymmetry compared to MS. CONCLUSION: Temporal parameters are the most sensitive to body asymmetry evaluation. However, range of motion is completely inappropriate if it is calculated for one movement cycle.

Association and heritability of traits of milk productivity and blood in the dairy cows

2020 ◽  
pp. 16-23
Author(s):  
S. A. Gritsenko ◽  
Yu. R. Sadyrtdinova
Keyword(s):  
Dairy Cows ◽  
Biochemical Parameters ◽  
Selection Process ◽  
Practical Importance ◽  
Correlation Method ◽  
Regression Method ◽  
Average Level ◽  
Total Protein Content ◽  
Milk Productivity ◽  
Straight Line

Numerous studies have shown that there is a certain association between the biochemical parameters of blood and milk. It is of big practical importance to determine the heritability of traits involved in the selection process, which gives breeders the opportunity to choose the direction of selection for the fastest solution of the tasks. The purpose of the researches was to establish the association between the indicators of the biochemical composition of milk and blood in the dairy cows, as well as to determine the heritability of the studied traits. It has been found in the course of researches that in most cases the correlations between the biochemical parameters of blood and milk were insignifi cant and unreliable. It can be seen that there is a slight correlation between the main indicators of blood and milk, which should be taken into account by breeders when conducting breeding to improve the quality of milk. The highest regression association has been observed between the content of carotene, calcium and phosphorus in blood and milk. If you increase these indicators in the blood by the corresponding unit, their content in milk will also increase by 0,90, 0,31 and 0,42, respectively. The heritability of milk productivity traits in most cases was at medium and low levels and ranged from 0,03 to 0,66 (straight-line correlation method) and from 0,03 to 0,44 (straight-line regression method). The heritability of hematological traits in most cases was at an average level and ranged from 0,14 to 0,98 (straight-line correlation method) and from 0,11 to 0,76 (straight-line regression method). The total protein content in the blood (h² =0,98 и 0,76) and the number of monocytes (h² =0,82 и 0,60) depended more on the genotypic features of the animal. The average level of heritability coeffi cients has been observed in the blood content of total lipids, phosphorus, eosinophils, young neutrophils, and lymphocytes.

scholarly journals The Analysis of Plantar Pressure Data Based on Multimodel Method in Patients with Anterior Cruciate Ligament Deficiency during Walking

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoli Li ◽  
Hongshi Huang ◽  
Jie Wang ◽  
Yuanyuan Yu ◽  
Yingfang Ao
Keyword(s):  
Anterior Cruciate Ligament ◽  
Human Body ◽  
Plantar Pressure ◽  
Cruciate Ligament ◽  
Lower Limbs ◽  
Pressure Data ◽  
Anterior Cruciate Ligament Deficiency ◽  
Gait Characteristics ◽  
Motion Function ◽  
Anterior Cruciate

The movement information of the human body can be recorded in the plantar pressure data, and the analysis of plantar pressure data can be used to judge whether the human body motion function is normal or not. A two-meter footscan® system was used to collect the plantar pressure data, and the kinetic and dynamic gait characteristics were extracted. According to the different description of gait characteristics, a set of models was established according to various people to present the movement of lower limbs. By the introduction of algorithm in machine learning, the FCM clustering algorithm is used to cluster the sample set and create a set of models, and then the SVM algorithm was used to identify the new samples, so as to complete the normal and abnormal motion function identification. The multimodel presented in this paper was carried out into the analysis of the anterior cruciate ligament deficiency. This method demonstrated being effective and can provide auxiliary analysis for clinical diagnosis.

Hyperketonemia GWAS and parity-dependent SNP associations in Holstein dairy cows intensively sampled for blood β-hydroxybutyrate concentration

2020 ◽  
Vol 52 (8) ◽  
pp. 347-357
Author(s):  
Ryan S. Pralle ◽  
Nichol E. Schultz ◽  
Heather M. White ◽  
Kent A. Weigel
Keyword(s):  
Dairy Cows ◽  
Metabolic Pathways ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Genome Wide Association Study ◽  
Enrichment Analysis ◽  
A Genome ◽  
Screening Protocol ◽  
Control Procedures ◽  
Nuclear Polymorphism

Hyperketonemia (HYK) is a metabolic disorder that affects early postpartum dairy cows; however, there has been limited success in identifying genomic variants contributing to HYK susceptibility. We conducted a genome-wide association study (GWAS) using HYK phenotypes based on an intensive screening protocol, interrogated genotype interactions with parity group (GWIS), and evaluated the enrichment of annotated metabolic pathways. Holstein cows were enrolled into the experiment after parturition, and blood samples were collected at four timepoints between 5 and 18 days postpartum. Concentration of blood β-hydroxybutyrate (BHB) was quantified cow-side via a handheld BHB meter. Cows were labeled as a HYK case when at least one blood sample had BHB ≥ 1.2 mmol/L, and all other cows were considered non-HYK controls. After quality control procedures, 1,710 cows and 58,699 genotypes were available for further analysis. The GWAS and GWIS were performed using the forward feature select linear mixed model method. There was evidence for an association between ARS-BFGL-NGS-91238 and HYK susceptibility, as well as parity-dependent associations to HYK for BovineHD0600024247 and BovineHD1400023753. Candidate genes annotated to these single nuclear polymorphism associations have been previously associated with obesity, diabetes, insulin resistance, and fatty liver in humans and rodent models. Enrichment analysis revealed focal adhesion and axon guidance as metabolic pathways contributing to HYK etiology, while genetic variation in pathways related to insulin secretion and sensitivity may affect HYK susceptibility in a parity-dependent matter. In conclusion, the present work proposes several novel marker associations and metabolic pathways contributing to genetic risk for HYK susceptibility.

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