Gait - Science topic

Chemical reactions inside water main cause due to heavy saditation, sanitation of garbage,industrial pollutants in this rainy season here.overflloded water with huge pollutants mixed with water.

This research is too lengthy and answer will take huge pages f

Gradually I will reply but research ongoing.

The horizontal components of GRF are actually the force of friction (more specifically, static friction). Based on physics, static friction exists as long as 1) the contact surface is not perfectly smooth, 2) there is a pressure force vertical to the contact surface, and 3) there is a tendency of horizontal movement between objects (e.g., foot and ground).

Hope this answered your question exactly.

@Carlo De Benedictis

Thank you.

I have also come up with a better way to determine the positive and negative of the stride width of natural gait.

If the left and right stride lengths have 0 intersection, then the corresponding stride width is positive.

If the left and right stride lengths have 1 intersection, then the corresponding stride width is negative.

If the left and right stride lengths have an infinite number of intersection points, then the corresponding stride width is zero.

Such algorithm can be easily achieved by using Matlab's polyxpoly function.

The knee reaction force during gait can vary depending on several factors, such as walking speed, individual biomechanics, and overall body weight. However, a commonly cited value for the peak knee reaction force during walking is around 2.5 to 3 times an individual's body weight. This value typically occurs during the stance phase of gait, particularly in the early stance, when the knee joint experiences the highest loads.

Keep in mind that these values are only approximate and can vary significantly between individuals. Factors like walking or running technique, footwear, and any pre-existing knee conditions may influence the actual knee reaction forces experienced during gait.

Reading suggestion:

SIGWARD, Susan M.; LIN, Paige; PRATT, Kristamarie. Knee loading asymmetries during gait and running in early rehabilitation following anterior cruciate ligament reconstruction: a longitudinal study. Clinical biomechanics, v. 32, p. 249-254, 2016.

OBRĘBSKA, Paulina; SKUBICH, Justyna; PISZCZATOWSKI, Szczepan. Gender differences in the knee joint loadings during gait. Gait & Posture, v. 79, p. 195-202, 2020.

ZALEWSKA, Paulina; SKUBICH, Justyna; PISZCZATOWSKI, Szczepan. Gender differences in the knee joint loadings during gait. Gait & Posture, v. 79, 2020.

SCHMITZ, Anne; NOEHREN, Brian. What predicts the first peak of the knee adduction moment?. The Knee, v. 21, n. 6, p. 1077-1083, 2014.

ZHAO, Dong et al. Correlation between the knee adduction torque and medial contact force for a variety of gait patterns. Journal of orthopaedic research, v. 25, n. 6, p. 789-797, 2007.

Good Studies!

Hello Alexander,

Whether the author is the mobster/Irish gangster Daniel J. (Danny) O'Leary living in the first thirty years of 1900, I barely think you could find this article on the web. There is some paper version kept by a diligent investigator, who knows.

Some interesting paper on your searched topics in attachment by:

231116.pdf (ojp.gov),

Gang Membership (ojp.gov),

A Comparative Study of Violent Extremism and Gangs (ojp.gov).

Links do not glue and so that I try to add files.

Best Wishes. Romina

Kinovea is one of good software for gait Analysis. It contains all essential motion analysis tools including slow motion  and reverse playback. 

Hi Murtaza, Luca is rigth.

You need to obtain kinematic and kinetic data.

If you want to obtain a joint moment, the approach is called "inverse dynamics". In this regard, you need to calculate each segment's position, velocity and acceleration.

Several papers can help you, but I suggest starting with these books:

In these books, you can find specific chapters for understanding inverse dynamics.

Best

Andrea

Hello Dennis Shavelson

Some journals will permit this and some will not. If there is any doubt with your selected journal, I suggest you may need to contact them directly. I would hate for them to say you have '"breached the rules" before you submitted it. I say this because sometimes I may have published the abstract from having presented at a conference and some journals say that this rendered my submission as "null and void'". I would just take it to another journal where it IS ok.

Hi Zhaleh

First question:

1. I need a pilot study, or

2. A similar study to yours

Second question:

It is better but not must to be the same to increase homogeneity of variances between groups

IT depends on the area which is affected , as MCA VS ACA OR PCA stroke?

need to identify area or artery specific gait disturbances.

Check with the Georgia Tech Behavioral Medicine department. I know they were doing studies on individuals' gaits.

answer submitted

Have a look at these examples : https://au.mathworks.com/matlabcentral/answers/178210-human-gait-analysis-heel-strike

https://www.youtube.com/watch?v=HZMjgFP0iFo

In the below page, some ideas are proposed in order to resize a video that may be useful to read.

Dear Beltagi,

There are many comparative studies are already available with 2D and 3D motion analysis. In reliability point, kinovea will be less accurate than 3D gait lab. But less accurate analysis we can 100% depend on this 2D analysis software because of user friendly and economic point of view.

Thank you Ramkrishna, I will check

What is the variable that most impacts according to patient reports or clinical tests

Patient reports are always of prime importance. In our facility we cannot have equipment all the tests / pts may not be able to afford comprehensive tests..so in that situation also patient reports gain importance.

no of episodes, duration of episode and accompanying symptoms are always helpful in making clinical decision. Then one can decide on whether to go with vestibular assessment or radiological.

issue with patient reports is, skill level of the clinician and time it takes to get all relevant information.

Regards

Kinovea is one of good software for gait Analysis. It contains all essential motion analysis tools including slow motion  and reverse playback. 

Dear Frédéric,

I believe that you'll need a healthy group to study the differences in kinematics and EMG, thus in order to have a reference group (here for instance the healthy one) if you should not find any value in the literature referencing normal value for the healthy patient. I also think that you could take the first value as a reference for the patients with altered gait cycles and then after treatment retest and see how the patient has improved compared to his or her initial value. I send you an article from Lencioni et al.(2019) which might be of interest to your research.

to my knowledge, this is the most comprehensive published data set treating gait:

Hi Bastien Forcione

Thank you for giving more clarifications of your project.

Unfortunately, I have not used this model. And I don't know a very good answer that helps you a lot. But here is what I am thinking:

In my opinion, it is very difficult to get a low relative difference between the prediction and the experimental measurement in such a complex biomechanical system (foot including soft tissue, bones on a contact interaction with a comparatively rigid body like the ground). Although the relative difference depends on how you define your validation metric, I think the difference of less than 20% is very good in this kind of experimental setup and modeling.

But In your case, if you want to use the model in the optimization, you can consider your model as a surrogate (a computationally efficient model that we replace with a complicated one like the full meshed FE model). So It is enough for us that the surrogate points out the local minimum and it does not necessarily need to predict the cost function with very high accuracy. So I suggest you build up your model with an approximately good predictive capability (error of less and 20%), solve your optimization problem, and then at the end, do the experiment with your optimized setup and show how much did you reduce the cost function in your optimized structure. And more importantly, what was your computational efficiency compared to the FE model (in fact, running the FE model of Foot with a contact interaction at least takes 17 hours using a computer featuring Core i7-6700 CPU @ 3.4 GHz and 32 GB RAM. You can see the reference that I mentioned in the previous response. So this computational efficiency would be your achievement).

I hope it would be helpful for you

Some more

Hi Pilar, I suggest you search in public databases as figshare, mendeley, etc. Also, we've been done some work about that, and we are commonly presenting the study's dataset as supplementary material. I think the ISB work group (gait probably) has something else.

Dear Abhishek Paul

These articles might help, have a look:

1. http://users.isr.ist.utl.pt/~jsm/SPARSIS/2019_Athira_ACM_CSUR.pdf

2. https://www.ei.tum.de/mmk/verschiedenes/tum-iitkgp-gait-database/

3. https://www.researchgate.net/publication/228881763_Gait_Recognition_in_the_Presence_of_Occlusion_A_New_Dataset_and_Baseline_Algorithms

4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085678/

5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146167/

6. https://arxiv.org/pdf/1903.10744.pdf

Kind Regards

Though too late, thank you for your providing the links.

Cheers,

Soran

Thanks for your answer. The problem with this model is that it requires to put plates on the foot. These plates would be hard to fit within a shoe.

Dear researcher

I see in this page an important relationship to your question, I hope you read it.

Best regards

Hi Fakhruddin,

I'm not sure if I follow you exactly, but I will at least attempt to provide some level of feedback. There are several locomotor control theories that provide additional perspective on how the integrated effects of the nervous system and musculoskeletal systems interact to control movement. For example, Sparrow and Newell (Psychonomic Bulletin & Review, 1998, 5 (2), 173-196) proposed a metabolic energy expenditure component to regulating movement. In my work with individuals with a spinal cord injury we used an extension of their theory, and the fact that walking may be an emergent phenomenon (co-authors went on to publish a good review on this: Gollie, Guccione, Overground locomotor training in spinal cord injury: A performance-based framework). I would suggest trying to be more specific with your question, especially if you're asking something mechanistic in nature. I hope this helps.

Good Afternoon Dr. Ezenwankwo---

If the individual is at a higher functional level, I would utilize the Falls Efficacy Scale - International to measure fear of falling. I might employ the Activities-specific Balance Confidence Scale (ABC) to measure balance confidence. Both are easy to administer in gait studies and demonstrate sufficient validity and reliability properties.

Thank you.

I will look into this further. Do you have any suggestions on what is recommended to preprocess my data before applying any DL techniques?

I am not sure if this will be of any help, but we have found that Western and Japanese marathoners have a vertical oscillation 50% greater than East African marathoners. East Africans are known to consume less oxygen than Westerners while running. We believe this is due to their smaller vertical oscillation. The vertical oscillation of Western and Japanese marathoners adds an additional 2.48 miles to their marathon.

Given appropriate gait event detection (e. g. by foot switch or marker dynamics), you could use the software ProCalc which is supported by Vicon! Here you can extract joint angles (and many other gait parameters) per step cycle in an automated way.

As far as I read, it's okay to get a body-matched volunteer do the tasks,

but you should consider differences between muscle attachment sites which may slightly differ force directions

and muscle's max force capacity which relies on muscle volumes.

Modifying Musculoskeletal model with respect to patient's MRI may do the trick.

Of course, level of accuracy needed depends on your research question.

Dear Dr. Washeem,

Nexus (Plugin Gait - Helen Hayes model) calculates the Euler angles for the 3 joint rotations (Hip and Knee), but it is only possible to view the graphs in this software. Vicon uses Polygon software to generate reports (graphs, images, videos and texts) :

Another option for printing graphs and extracting information is the software Report Generator (Motion Lab Systems Inc) - you can try to evaluate a demo version of the software :

Best Regards,

Wagner de Godoy

Including acquisition of bioelectrical signals (EMG,EEG), in addition to IMUs, could be of help, if the assessment of CNS strategies for balance control is of interest. A recent paper about that:

Best Regards

--

Jorge Airy Mercado

Dear Rahul, in accordance with Maxime, could you precise your question please?

Hello!

I don't know any on that topic, but maybe you can find something useful here: https://datasetsearch.research.google.com/

Best and good luck!

Cristina

Performing a meta-analysis with numerical findings of pre-post studies is not advised and the main reason is that scores at baseline and post-test results are not independent of each other. For a full methodological explanation of why pre-post effect sizes should be avoided in meta-analyses, take a look at this paper:

If I was in your shoes, I would check whether there is a sufficient number of relevant controlled trials on the topic, and then I would only pool their results (post-test/change-from-baseline scores of intervention groups vs post-test/change-from-baseline scores of comparison groups), thus excluding uncontrolled studies from the quantitative synthesis.

This link may help.

For sure you may consider using a combination of BLE sensors combined with a smart phone app ... both MbientLab (https://mbientlab.com) and NOTCH (https://wearnotch.com) provide developer resources and examples ... Im using them to pilot study movement/gait analysis in connection to rehabilitation ... hope this helps ....

Dear Wagner de Godoy,

The processing was successfull.

We took a static trial, labelled and used the static plug-in gait (run static gait model + static subject calibration) and then did the dynamic trial. After labelling and processing (core processing + gait cycle events + butterworth filter-model outputs) we received the model outputs we were looking for.

Thank you very much for your support.

Kind regards,

Lara Wolff

Water availability – both now and in the future – is of the utmost importance.

However, the role of forests, their impact on precipitation, water yield and the hydrologic cycle more generally remain hotly contested. Afforestation strategies to ameliorate dry season flows have come under increasing scrutiny and attack.

Several major articles from the past decade and beyond conclude the impact of reforestation or afforestation on water yield is negative: additional forest cover will reduce and removing forests will raise downstream water availability. A second group of authors argue the opposite: planting additional forests should raise downstream water availability and intensify the hydrologic cycle. Obtaining supporting evidence for this second group of authors has been more difficult due to the larger scales at which the positive effects of forests on the water cycle may be seen.

Tree type can also impact the local water balance. Eucalyptus trees in particular have been criticized in the more arid regions of Africa for their heavy drain on available water supply. Deciduous tree species typically generate less ET than evergreen, potentially mediating forest impact on the local water balance. Overall, however, regardless of the tree species, the effect on the water balance is typically assumed to be negative.

Forests also have the ability to passively ‘attract’ or ‘catch’ atmospheric moisture, in particular, humidity in fog and clouds. Condensation on plant surfaces provides additional moisture for tree growth. Estimates suggest that anywhere from 200 mm year−1 to 425 mm year−1 additional moisture can be obtained through fog condensation. Some also find a positive correlation between the surface roughness of forests (varied age class) and drag coefficients, a precursor for potential precipitation. Equally important, a share of the moisture captured from the atmosphere in this way is again returned to the atmosphere as ET and remains available for vegetation growth in other areas.

Changing land-use patterns, both in the developing and in the developed world, should be subject to increased scrutiny. Progressive deforestation and wetland destruction have direct implications for the global hydrologic cycle. In this regard, maintaining and/or significantly increasing current levels of forest cover seems advisable. Deforestation, due to its impact on the ET regime, on soil degradation and loss, and reduced soil water retention represents a significant threat to planetary survival. Increasing forest and wetland cover is likely to have beneficial feedbacks on regional water budgets. Thus, along with accepted forest ecosystem functions (such as carbon sequestration, climate mitigation, biodiversity preservation and fossil fuel substitution through bioenergy), forests play an important role in helping manage the world's water regime.

Finally, Forests … play a major role in the atmospheric circulation and the water cycle on land and may have a role in mitigating regional climate, desertification and water security problems.

Sokratis Dimitrios Komaris

your comment was really helpful... so, second derivation of a marker position could be an standard acceleration of a point. an accurate accelerometer could measure it so I can use marker position instead of accelerometer data.

Uri Gottlieb

As I do not work much with EMG's, possibly I can be of assistance as I can apply my experience with lower extremity kinetics, kinematics and kinesiology to offer that the most important muscle engines to monitor are posterior tibial and peroneus longus for your study. These are the primary balance and stabilizing muscle engines of the feet.

Too often, Gastrocs, Anterior tibial and Soleus are monitored. Unfortunately, these muscle engines are compensatory and would be late to tell tales and be a good location for treatment and monitoring.

Hi Alireza,

First, what is the type of motion capture system do you have? Most of them actually have their own synchronization box, which serve as trigger in or trigger out for other external device including IMU. However, if your IMU sensor is a standalone sensor without any base to connected, then you can try an option to synchronize it by using some movement that cause spike on IMU signal like jumping.

Hope this helps you

Interesting

Dear Bruno Chrcanovic ,

Thank you for this very important information for me as a graduating student, who has not yet published on research Gate (RG). So budding researchers should watch out for these groups of people you just mentioned. I did not know as such if we could constitute a mafia on the network to extract money. Know that your comment will serve me as a lesson when I have to start by publishing my articles.

Good work!

For those who may be interested, we have recently published an open access dataset of kinematic (including joint angles), kinetic and EMG individual data of 50 healthy subjects (age range 6 - 72 yrs) during different locomotor tasks: walking at different speeds, stiars ascending/descending, toe/heel walking. The dataset is published on Scientific Data Journal and can be freely downloaded at this link:

Yes, and if i am correct with what exactly you want, if you want to differentiate gait pattern from elderly population then you need another group for comparison so that you can run statistical analysis between those two groups from the any parameters you have calculated. You can refer some study for that: https://www.sciencedirect.com/science/article/abs/pii/S0003999300900388

However, the current trend for differentiating between gait pattern was changed to faster and more accurate method like using machine learning or deep learning with data from wearable sensors.

What is the problem you want to solve in human gait with accelerometer/ IMU?

Gait event detection? or maybe gait pattern classification?

After you decide what problem in gait you want to solve, then you can go for specific data processing and analysis.

There is a lot of paper discuss about detect gait event using IMU or classify gait pattern with IMU.

ISB recommendations on the reporting of intersegmental forces and moments during human motion analysis

Journal of Biomechanics - Volume 99, 23 January 2020, 109533

No clear consensus exists about the best methodology to compute MLE. Regarding motion capture methods, many studies use the C7 or T6 markers to compute trunk velocity. Others use hip/knee/ankle angles. A very good reference to have an overall survey of existing methods is the recent systematic review by Sina Mehdizadeh. Check the supplementary file that gives details about the methodology of each study.

I would be careful to state that there is a "best" device but rather suggest to try to find the "right choice" depending on the research question/application. Therefore, you should know about the technical specifications and properties of the different devices which will inform you about advantages and disadvantages or certain limitations.

Agreed, the F-Scan is thin but you have to realize that it is based on a Mylar sheet that is flexible in one bending direction but does not conform well to 3-d curvatures as you might find them in foot orthoses. The F-Scan will crinkle which may cause artefacts. (We have investigated and described these issues in our 2006 Clin Orthop & Rel Res paper, Martinelli et al.)

Therefore, even though the Pedar is thicker, it is better suited because their capacitive insoles adapt to the shape of orthoses quite well without crinkling. I have been using Pedar insoles for a long time and in even more extreme loading situations and have often observed how well the insoles "mold" over orthoses even with more pronounced 3-d shapes..

It is simple, reliable but forgotten method to predict frailty. Just you need to know distance and Stopwatch

You can use the Matlab function interp1 to perform spine interplation. It will preserve signal's shape with the desired number of points.

See my article that applied this method for modifying stride durations within acceleration signals:

Thank you all for your responses!

The cheapest is likely to be either a 2D video camera and free software.

The trouble you will find is placing a camera in the correct location. Using a treadmill is unlikely to be a good move with this patient group, therefore you will need multiple cameras to catch more than a step or two initiation of gait.

You could try an app on a mobile phone, you can either find one that tracks movement or one that streams data via Bluetooth. Most phones have both at least one triaxial accelerometer and gyroscope included, so depending on your skills with signal processing this could be a reasonably cheap approach.

This article studied a 12h period of THA patients' daily activities.

In this case, HIP98 compact disk also has valuable data.

https://www.sciencedirect.com/science/article/abs/pii/S0021929001000355

https://orthoload.com/test-loads/data-collection-hip98/

Fabien Leboeuf

great, thanks for the hint. Looking forward to seeing the results of the mentioned paper.

Best regards,

Linard

Hello Dilly de Silva

Gait belt is an assistive device and is meant for easy ambulation of the patients and to prevent falls. The force and the body weight transfer during gait is facilitated by the use of this belt. The griping power of the therapist increases and thus prevent the risk of fall. Same time the energy of therapist of preserved due to the assistance by gait belt.

Best Regards

NR MOHANTY

I can see what you mean.

But I think explaining a large variance in number of steps would be easier than explaining why you decided to omit some of your data.

Statistically speaking, you will probably reduce the number of steps to a single number (average, variance, etc.), so it has no meaning from which number of steps this parameter was calculated.

I do think you'll have to mention the variance in number of steps between subjects, but that can be regarded to technical problems resulting in non valid steps (which also needs a definition and explanation - why 70% of your data was invalid)

Good luck!

I think you can use this plugin.

Best regards,

Pierre

David Oulton Thank you so much for your answer, it has removed some of ambiguity

Dear Dr. Elsayed,

You can find references of gait analysis systems (optical and inertial motion capture, electromyography and force plates) at the link below :

Some recommendations on the construction of a facility for the gait laboratory are described in the two attached files.

I hope this information is useful.

Best Regards,

I contacted him even before asking a question hear. Have not heard from him/ his team yet.

It is possible if you have a dynamometric force plate,but not on a piezoelectric plate. But you have to measure one foot and after the other foot in two different tests. And it is easier to measure the COP on a balance test than in a walking test.