Gait analysis

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The gait analysis (ger .: gait analysis) is a technical and scientific methods - Part field of motion analysis by means of which the natural locomotion of creatures, especially the man, the - Walking is described and evaluated for its characteristics out. It can be used for research (e.g. movement analysis), diagnostics (e.g. finding the causes of a gait disorder) or documentation (e.g. for quality assurance ).

In the instrumental gait analysis, for example, step length, walking speed, step frequency, joint angle, forces acting on the joints, muscle activity and energy consumption are evaluated.

Investigation methods

Representation of leg movements during a step cycle

In gait analysis, kinematics processes (optical processes, for example: motion capture for movement tracking using cinematography , video, etc. - recording of the visible sequence of movements), kinetics: ( force measurement , for example floor reaction forces) are used in gait analysis. and electromyography (innervation patterns of the muscles).

Marker-based analysis

Markers are given to the subject, i. H. small reflective spheres glued to the skin at defined points. Typically on the legs and torso. In addition, electrodes are often stuck on in order to measure muscle activities with so-called electromyography . Then the test person is asked to walk a defined distance. Force measuring plates are (mostly) embedded in the ground along the way , with which the ground reaction forces can be measured when the test person steps on the plate. Ideally, the test person hits the middle of the plate with one foot and the middle of the next plate with the other foot during the next step.

The cameras are distributed in the room in such a way that the position of the person to be examined can be “seen” by at least two cameras at any time in a fixed observation volume. Then the position in three-dimensional space can be reconstructed.

Alternatively, gait analyzes on the treadmill are possible, although it is known that individual parameters for walking freely on the walking distance differ.

It is known that a source of error in marker-based analysis lies in the fact that the skin and thus the markers shift in the course of movement compared to the bone skeleton.

Kinematic methods

All photographic processes with the help of which movement sequences can be recorded and reproduced are included in the kinematic methods. These were initially - at the end of the 19th century - chronophotographic ( EJ Marey , 1830–1904) and later film recordings. The digitization of these recordings required for the calculation of scientific data was very complex. It could only be replaced by automatic evaluation methods in the second half of the 20th century. Since then, video and marker-based infrared recording methods (not raw data) have become established for motion analysis - also because they are less dependent on the light conditions in the recording room. Due to the rapid technological progress since the beginning of the 21st century, more and more processes are coming onto the market which represent more modern alternatives to conventional systems and offer more possibilities. Image-based systems that can extract information on the basis of images (raw data) are of particular interest. The latest systems, by extracting the patient's silhouette, do not need any markers. In combination with conventional marker tracking, there are advantages which, in addition to the positive time aspect, improve the accuracy and reliability of a gait analysis.

Kinetic Methods

Floor reaction force in 3 dimensions. Measured during a step cycle by a force plate

Kinetics deals with the effect and measurement of forces. The gait analysis measures the reaction force ( counterforce ) of the floor to the force that the body transmits through the feet when stepping on the floor. To measure this reaction force, a force plate originally designed for this purpose is used ( see also: Pedography ). There are two different technical methods of measuring force. One uses strain gauges , the other the force is absorbed by piezo crystals . The reaction force is recorded as a three-dimensional force vector over the entire force plate. It consists of a vertical and two shear force components (see also: Shear ) that act along the surface of the force plate. In order to be able to make statements about the course of the force under the foot, you need a point where the force components are concentrated at every moment. This point is known as the Center of Pressure ("CP") . The curve of its course is one of the most important parameters in gait analysis. This curve, known as the hydrograph , can be evaluated in terms of its length and position as well as its course over time.

However, this form of measurement does not provide any information about how the reaction force is distributed with respect to the sole of the foot. However, this can be important information if, for example, there are problems with balance. For this reason, special mats or insoles were developed for the shoes. In most cases, capacitive elements (see: electrical capacitance ) are used, with the help of which the pressure distribution under the foot can be measured when standing or walking.

Electromyographic methods

Representation of the muscle activity of the main leg muscles during a gait cycle

The activity (contraction) of muscle fibers creates electrical potentials. These can be recorded over the skin using sensors ( electromyography (EMG)). This allows the duration of the innervation to be determined. The action potentials of the active muscle fibers can be measured with the aid of electrodes that are attached to the skin above the relevant muscle. The result is a total potential, the (signal) strength of which is dependent on the number of activated muscle fibers and their distance from the electrode. The measured strength of the signal is therefore not very meaningful - but this can be achieved through specific measures. For gait analysis, it is only important to assess whether and when a muscle is active. This can be achieved by determining the threshold for the EMG signal.

Inertial sensor-based methods

In contrast to video-based analysis methods, the use of inertial measuring units enables the ubiquitous use of gait analysis systems at the expense of lower local resolution. The number of measurement units used varies, but these are often attached to the foot, lower leg and / or lower back.

Data analysis

With the help of the data obtained with the methods described, the walk of the test person can be reconstructed in the three spatial dimensions and in time. Not only the speeds and accelerations of the limbs and the angle between the limbs are calculated, but the forces acting in the joints and the performance achieved there can also be calculated using the methods of inverse dynamics. For the latter, however, personal data of the person examined such as height, weight , partial masses of the limbs and their moments of inertia are required (see also: Mathematical Models of Biomechanics ).

To diagnose a gait event (= evaluation of all data), the gait is first divided into its repetitive sections (cycles) of steps or double steps. These cycles are obtained, for example, from the data from two contact switches that are placed under each foot under the heel and under the ball of the big toe. These signal the touchdown of the foot (heel) and the lifting of the foot at the end of the step (ball of the big toe). If inertial measuring units are used instead of contact switches , the division into cycles can be done, for example, using peak finders , dynamic time warping , local cyclicity estimation or hidden Markov models .

In the individual step, a distinction is made between the stance and swing phases. These phases can be further subdivided. The stance phase is divided into weight transfer, from the first contact to the lifting of the other leg, the middle stance phase from standing on the whole foot to lifting the heel and the end phase when the other leg touches the ground. The swing phase begins with the lifting of the big toe. The swing begins when the swing leg passes the standing leg, then the middle swing part (mid swing) until the lower leg is perpendicular to the ground and finally the final swing, which lasts until the heel touches down. A gait cycle is thus ended.

The stance phase takes up about 60% of the time of the gait cycle, the swing phase 40%. Since this applies alternately to both legs, there are two overlapping phases in which both feet are on the ground, each of which takes up around 10% of the gait cycle time. All data collected are standardized to these times.

The data that can be used in instrumental gait analysis to document gait and movement patterns include step length (right / left), walking speed and step frequency, the angle of the joints and the forces acting on the joints, the activity of the muscles and the energy consumption. In the case of the inertial sensor -based method, various methods of sensor data fusion or neural networks are used for this purpose .

For different groups of people (age groups, height / weight, pathologies etc.) there are standard values ​​for certain parameters with which a gait that is currently to be assessed is compared.

Goals of gait analysis

The aim of the gait analysis is, on the one hand, to be able to draw general knowledge about the movement sequence of the gait pattern and thus to draw conclusions about its development (neuronal and mechanical). In particular, it then has the goal of analyzing a person's gait on the basis of this knowledge and assessing how far his gait corresponds to the "normal" gait or whether it deviates from it. A decision must then be made as to whether the observed deviations can have pathological causes and how these can be corrected, if necessary, by therapeutic (e.g. surgical or physiotherapeutic (see physiotherapy )) or technical measures ( using orthoses or prostheses ). It must also be considered whether the gait pattern deviates from the "norm" due to individual biomechanical variants (for example the Sklet system). The first part (general knowledge and conclusions about the development) is a sub-area of ​​motion analysis.

Motion analysis

Markers (white) for kinematic analysis and electrodes and preamplifiers (blue) for EMG (muscle activity) analysis

As a branch of movement analysis, the goal of gait analysis is to find out how the neural connections that are created in the central nervous system enable animals and humans to walk. An attempt is also made to infer how these can be changed through practice (learning). This goal can e.g. B. by analyzing and modifying (see: learning to move ) the muscles involved in gait (see: muscles ) and their temporal activity.

In addition to the use of the biomechanical (see biomechanics ) methods mentioned, comparisons with the gait of animals - four-legged and two-legged - and the tracking of the development of two-legged walking in humans - historically - in the course of evolution and individually, from the first steps of the toddler used up to the mature walking of the adult human.

By examining the change in gait pattern in the case of known disorders or damage to the central nervous system , conclusions can also be drawn about the interconnection and the importance of certain brain and spinal cord sections (see: spinal cord ) on gait behavior. In addition to these investigations, targeted interventions in the central nervous system of test animals ( e.g. cats, see: Sten Grillner ) are also carried out in animal experiments (e.g. cutting of the upper spinal cord or the brain stem ) and their effect on the gait behavior of the animals is examined . The findings from the results of these examinations are of direct benefit to rehabilitation .

Fall prevention

The analysis of gait behavior can also be used to find possible fall risks for a test person , to analyze their causes and to develop possible measures to reduce the risk (see also: Physiotherapeutic measures for fall prevention ). Falls, especially in older people - with sometimes fatal consequences - cause considerable costs in the medical system today.

The step-to-step variability - the extent of a change in step length from one step to the next - indicates an increased risk of falling. According to the results of a 1997 study, a 1.7 cm difference in stride length, which is barely noticeable to the naked eye, doubles the risk of falling in the next six months by 50%.

Development of prostheses for the lower extremity

Another area of ​​application for gait analysis is the development, testing and improvement of prostheses for the leg or parts of the leg. This sub-area developed after the First World War , in which many soldiers lost one or part of their legs. Today this area also plays an important role, because as a result of diabetes it is often necessary to amputate legs or their parts. An important task of gait analysis is to determine the energy that must be applied by the gait of the prosthesis wearer for the gait. The aim is to use this to develop improvements to the prosthesis that minimize this energy consumption. It helps if you can determine the flow of energy between the individual limbs.

rehabilitation

Gait analysis is used in many areas of medicine, especially medical rehabilitation. In rehabilitation, it is used to analyze a pathological gait pattern so that the cause of this pathological movement sequence and then, if possible, a therapy can be found. The gait analysis after the therapy has been carried out is also used to assess, according to objective criteria, which changes in the gait pattern have resulted from the treatment.

Typical gait disorders can arise from problems of the musculoskeletal system (acute: injuries, chronic: degenerative processes in bones, joints, muscles, tendons, e.g. rheumatism ) or from neurological problems, central (brain diseases), or peripheral, for example sensory - vestibular (for Example balance disorders), visual etc. The peripheral problems in children result mainly from infantile cerebral palsy or dysmelia and muscular dystrophy . In adults, the causes are usually brain diseases such as Parkinson's disease (see: Parkinson's disease ), multiple sclerosis or other diseases that lead to ataxia , or they are the consequences of a stroke .

In rehabilitation, however , the instrumental gait analysis is not the only basis for assessing a gait pattern. The assessment by a therapist experienced in this matter plays an equally important role . The instrumental gait analysis only assesses the mechanical parameters of the gait and often only those of the lower extremities as well as those of the head and trunk. Equally important, however, is the overall impression of the gait , which also allows statements to be made about other than just mechanical characteristics (such as emotionality , restlessness) and whose correct assessment can contribute to successful rehabilitation.

History of the development of gait analysis

Historical beginnings

The first report in our western culture on thoughts about human walking can be found in the work of Aristotle (384-322 aC) ( De Motu Animalium ) on the movement of living things . Aristotle thinks about how - from a physical point of view - a movement can even come about and recognizes that a counter - i.e. reaction force - the reaction force of the floor - plays a decisive role when walking. The work of Giovanni A. Borelli (1608–1679), also entitled: De Motu Animalium , can be described as the beginning of a scientific analysis of walking in Europe . He wants to show how the laws of mechanics, especially leverage, can be used to explain the movement of living beings. Comments on man's gait can also be found in Luigi Galvani (muscle actions) and Isaac Newton (mechanics).

An intensive scientific study of human walk took place in the 19th century. An early work by M. Carlet on the human walk ( Etude de la marche ) appeared in France in 1872. The work of Wilhelm Braune and Otto Fischer, who were commissioned to investigate how the weight of the baggage affects the gait of infantrymen, then continued. They had already carried out some preliminary investigations into the gait of humans and could also refer to the work of z. B. fall back on the brothers Wilhelm and Eduard Weber, who had already published a book in 1836 about the 'mechanics of human walking tools'.

Braune / Fischer observed that the movement of the legs is a pendulum movement and that its speed does not depend on the strength of the muscles, but on the length of the legs and the external force acting on them, generally gravity. With the help of eleven Geissler tubes , which they attached to the body parts (two each on the feet, lower legs, thighs, forearms and upper arms and one on the head), and a chronophotography plate , they were able to determine the spatial coordinates of the walking movements, as well as the coordinates of the Joint centers, their trajectories, as well as rotations and deformations of the torso and hips. They did not consider the differences in the gait pattern of unloaded and loaded people to be serious.

The further development of photography by Étienne-Jules Marey (1830–1904) with chronophotography was helpful for further research into the human gait . With this method, up to 12 pictures were taken in a row within one second. The camera ( photographic gun ) remained aimed at the same object, creating a plate with 12 successive phases of movement. Marey made such recordings of many animals in the air (birds, insects), on land (sheep, donkeys, elephants, etc.) and in the water (fish, mollusks, etc.) In this way, Marey studied the technique of their locomotion. Marey also took such pictures of people walking and running.

Around the same time as Marey, Eadweard Muybridge (1830–1904), a British photographer who spent much of his life in the United States, continued to develop photography of the movement. He became known for taking photos of animals in motion. In order to optically “capture” these movements, he used several cameras placed side by side.

After the First World War, and especially after the Second World War, with the large number of veterans who had lost their legs or parts of their legs during the war, technical gait analysis became particularly important for the development, testing and improvement of prostheses . Due to the financially better equipment of the laboratories and the technical, especially electronic, developments, initially in the USA, a number of instruments, especially in measurement technology, could be developed for gait analysis, especially kinematics and kinetics , were useful.

kinematics

Kinematics is concerned with the geometric movement relationships of bodies, their parts or individual points. It examines their position (trajectories), speeds and accelerations as a function of time. Measuring a distance as well as the step length is one of the elementary tasks of gait analysis. They could be made after performing the gait that was to be assessed. In order to determine angles, speeds and accelerations that are constantly changing during the course of the gait, specific procedures are required to achieve this.

There were initially mechanical, then electronic protractors (goniometers) that could be attached to the joints, for example the knee, as well as accelerometers that were mounted on the limbs, for example the shin. However, these often led to the test subject's natural gait being distorted. Eventually, it became generally accepted that the kinematic data was collected with the help of photographic processes. For this purpose, as von Marey, photo plates could be used which were exposed several times at known time intervals. To make the body parts easier to identify and measure, reflective strips were stuck to the body parts (legs and torso), which were illuminated by a stroboscopic light source. This made cinematography, i.e. film recordings, the suitable technique for such investigations. It was further developed based on the work of Marey and Muybridge.

In the beginning it was time-consuming and error-prone to extract the necessary data from a film recording. The coordinates of the required points had to be determined from the individual recordings on the projection surface. To do this, you must first decide which are the important points that you need for further processing. In the motion analysis, these are mainly the center points of the joints. Lengths, angles and paths can then be calculated from the relationships between the determined coordinates, as well as the translational and rotational speeds and accelerations taking into account the time that has passed between the individual recordings (images) of the film. For a long time, this extraction of the coordinates had to be carried out by hand. The so-called markers, which were stuck to specific test subjects in order to obtain an estimate of the joint centers, were therefore a relief.

However, determining these joint centers posed another major problem. They are located within the joints and are therefore not visible from the outside - an attempt was therefore actually made to determine these points by driving nails into the joints. But because of the great pain for the subjects, this procedure was soon discontinued. - Since then, one has tried to determine the joint centers as best as possible - and with increasing precision - from knowledge of the anatomy. Another problem was and is that these markers shift during movement and therefore do not always show the exact center of the joint. The latest technologies bypass these sources of error and contribute to further progress. By extracting the subject's silhouette from the room, possible error potentials (marker shift, marker obscuration, etc.) are eliminated. The additional integration of markers, which automatically stabilize the detection of the silhouette, also generates exact data for special movements in which the silhouette does not change (e.g. inversion / eversion).

Until the 1970s, the film recordings were only made in the sagittal plane (side view). The development of DLT (Digital Linear Transformation) then made it possible to combine the data from initially 2 cameras, which recorded the subject's walk at right angles to each other, to form a 3-dimensional image. These and similar advanced mathematical processes make it possible today that the data from almost any number of cameras can be evaluated to form a 3-dimensional image, which can then be viewed and analyzed from any angle. Today, up to 12 cameras are used, depending on the need and size of the system. However, since this means a lot of computing effort and thus also time, an attempt is now made again to obtain all the necessary data - with the necessary precision - with a minimum of cameras. Various file formats can be used for further processing of the data. Usually this is the raw data format, with each camera manufacturer (infrared and image / video) mostly using their own formats. It should be noted that saving data in certain formats can cause data to be lost. In this way, the manufacturer should ensure which formats are used.

For this reason, an interest group has been formed under OpenRAW.org that calls on camera manufacturers to unrestrictedly disclose the raw data formats, which would enable the user to access his raw data for many years to come, without being in possession of the previously functioning software process and, if necessary, be able to write a program to support its now outdated format.

kinetics

Kinetics deals with the movements of bodies under the influence of external and internal forces. Isaac Newton's 3rd law of motion (actio = reactio) (see actio and reactio ) forms the basis of the kinetic analysis of gait. Even in their time as hunters, humans judged the animals in their environment according to their footprints, because they were able to draw conclusions about the mass and weight of the animals.

When people walk, gravity and the reaction force of the ground must be taken into account as external forces , as well as muscle forces as internal forces. Since the magnitude of gravity corresponds to the reaction force of the ground on which a person walks, this reaction force is measured for the gait analysis. In order to be able to do this, different methods were developed and tried out in order to first assess this reaction force of the soil and later to measure it as precisely as possible.

Carlet (1872) used e.g. B. air chambers to be able to assess the pressure of the heel and forefoot when stepping on and already received the 2-peak curve from this, which we also get today when measuring the force vectors of force plates. However, Carlet's curve could not be broken down into the three dimensions of space. Braune / Fischer (1895) tried to develop the 3 force components through their kinematic data.

The first attempts at the beginning of the 20th century to measure the reaction force while walking used pneumatic methods ( e.g. Marey ), some of which were embedded in the shoe. The first mechanical force measuring platform (see Biomechanics ) was designed by W. Fenn. In 1934, H. Elftmann developed a force measuring platform that consisted of two plates connected with four calibratable springs. This enabled him to measure the vertical force and the shear forces in the sagittal plane. He was also the first to discuss the interplay of potential and kinetic energy in people's gait and to think about the torques and influence of muscles that pull over two joints.

DM Cunningham and GW Brown developed the first force measuring platform based on strain gauges in the USA in the early 1950s , with the help of which the ground reaction force could be broken down into its spatial components. It has been used in some laboratories in the United States.

Around the same time in Europe, J. Paul at the University of Strathclyde (Scotland) also developed a force measuring platform based on strain gauges. He used them mainly in his laboratory to determine the forces that are transferred in the joints when walking (see above); this is important for the design of prostheses .

Around the same time in Europe, J. Paul at the University of Strathclyde (Scotland) also developed a force measuring platform based on strain gauges. He mainly used them in his laboratory to determine the forces that are transmitted in the joints when walking (see above). Knowledge of these forces is required in order to calculate the energy that the prosthesis wearer needs to walk. It is an important criterion for the construction and adaptation of a prosthesis that the energy that the prosthesis wearer has to use in order to be able to walk with the prosthesis over a longer distance is as low as possible.

To determine this energy, the energy that is generated by the individual limbs (segments) or transmitted from one to the next must be calculated. These energies can be calculated using the inverse dynamics method. The inverse dynamics method was developed in the 1970s by D. Winter (Waterloo / Canada) for gait analysis. Winter describes it in detail in his book The Biomechanics and Motor Control of Human Movement .

In addition to the measured kinematic data and the kinetic data of the forces and moments from the force plates, anthropometric data of the prosthesis wearer are required for this calculation.

Today, commercial force plates based on strain gauges are primarily manufactured and sold by the American companies AMTI and Bertec . In the 1960s, some researchers in the USA tried the ground reaction forces with the help of piezo crystals (see piezoelectricity ), in which forces can be measured by the charge shifts of the crystals. However, there were difficulties because these charge shifts equalize each other immediately after the measurement process and therefore could not be used for a recording. This problem was solved in 1969 by the Kistler company in Switzerland, whose force plates are now standard in a scientific gait laboratory. A force measuring plate was also developed by the Kistler company in the 1990s - which requires some design and measurement changes - which can be integrated into a treadmill. This enables gait analysis on the treadmill.

Electromyography

Another technique that helped to analyze the gait more precisely was developed with electromyography (measurement of muscle action potentials = activity of muscles). This method was developed for these patients by the group of Verne Inman (San Francisco) after a few epidemic-like incidents of poliomyelitis in the USA in the 1950s. In order to be able to determine whether the muscles in question were innervated, i.e. whether they were active, needle electrodes were inserted into the muscles. The needles were relatively thick and inflexible and caused considerable pain to the patient. At first only the electrical activity of a single muscle could be observed. For this purpose, the signal was first fed into the soundtrack of a film recorder and evaluated from there, later it could be photographed or filmed by the oscilloscope. Then the signal had to be evaluated by hand like a film recording. So that the stress - especially the pain - could be limited for the test subjects, increasingly thinner and flexible wire electrodes were developed that could remain in the muscle between the individual analysis events, i.e. they did not have to be repeatedly inserted.

When one was then able to derive and record the activity of several muscles simultaneously via different channels, this technique also became interesting for gait analysis. However, the procedure was still very painful for the patients because the muscles contract severely while walking, injuring the muscle tissue. Wire electrodes are therefore only used today if one wants to examine the quality of the contraction of individual motor units or muscle fibers .

With the development of surface electrodes, which no longer had to be inserted into the muscles, but stuck to the skin above the muscle to be examined, the total potentials of the active motor units in the receiving area of ​​the electrode could be determined. This enabled electromyography (EMG) to become a routine procedure in gait analysis. Today, the activity of up to eight muscles on each side of the body is usually analyzed.

However, the problem remains that the signal must be recorded directly on the body, i.e. the data must be transmitted from the subject's body to the evaluation device. Newer measurement systems integrate radio transmitters into the EMG electrodes, so that the patient can walk without being hindered by cables. The problem with this, however, is that the signals then have to be amplified on the body and the transmitters may become so large and heavy that they affect the subject's gait.

If cable systems are used, examinations in an aisle laboratory usually have a rail above the aisle, in which the EMG cables, combined in one cable, run and are routed to the evaluation computer. On the test subject, the cables from the individual discharge points above the muscles are usually amplified by small, lightweight preamplifiers and routed to an equally small and light box on the test subject's back. There they may be reinforced again and transported to the “guide” rail in another, larger cable.

literature

  • J. Perry: Gait Analysis . Second Edition, Slack Incorporated, 2010
  • Michael M. Whittle: Gait Analysis - an Introduction . Second Edition, Butterworth Heinemann 1999.
  • Wilhelm Braune, Otto Fischer: The walk of the people . Teubner Verlag Berlin 1895.
  • Wilhelm Braune, Otto Fischer: Der Gang des Menschen ( The Human Gait ). Springer Verlag New York 1987 (reprint).
  • M. Calet: Sur la locomotion humane Etude de la marche . in: Annalen der Wissenschaftlichen Naturwissenschaften 1872 Vol. 5, Series: Zoologie 16: 1.
  • Grillner, Sten Control of locomotion in bipeds, tetrapods and fish . In: Brooks, VB (Ed.) Handbook of Physiology , Section I, Vol. 2, Motor Control , pp. 1179-1236. Bethesda (1981). MD: American Physiological Society
  • Grillner. Sten, P. Sanger: On the Central Generation of Locomotion in the low spinal Cat . In: Experimental Brain Research . 1979. pp. 241-261.
  • Forssberg, Hans: Ontogeny of human locomotor control I: Infant stepping, supported locomotion and transition to independent locomotion . In: Experimental Brain Research 57 (1985): 480-493.
  • Forssberg, Hans, Sten Grillner, J. Halbertsma: The locomotion of the low spinal cat. I. Coordination within the hindlimb . In: Acta Physiologica Scandinavica 108, 1980. pp. 269-281.
  • Forssberg, Hans, Sten Grillner, J. Halbertsma: The locomotion of the low spinal cat. II. Interlimb Coordination . In: Acta Physiologica Scandinavica 108, 1980. pp. 283-295.
  • David H. Sutherland: The evolution of clinical gait analysis part I Kinesiological EMG in: Gait and Posture 14 (2001). Pp. 61-70.
  • David H. Sutherland: The evolution of clinical gait analysis part II: Kinematics in: Gait and Posture 16 (200) 2 pp. 159-179.
  • David H. Sutherland: The evolution of clinical gait analysis part III: Kinetics and energy assessment in: Gait and Posture 21 (2005). Pp. 447-461.
  • Ludwig, Oliver: Gait Analysis in Practice - Application in Prevention, Therapy and Care C. Maurer-Verlag, Geislingen, 2012.
  • David A. Winter: The Biomechanics and Motor Control of Human Movement . Second Edition, John Wiley & Sons New York 1990.
  • David A. Winter: The Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological . Waterloo, Ontario: University of Waterloo Press. 1991.

Individual evidence

  1. ↑ Ludwig, Oliver: Gait Analysis in Practice - Application in Prevention, Therapy and Care C. Maurer-Verlag, Geislingen, 2012, p. 106.
  2. ↑ Hamen Parul Shukla, "Proposal of a passive marker set for Pediatric gait data analysis", University of Toronto, 2000. Section "2.3 Skin movement artefact", pp. 41-42.
  3. ↑ Michael W. Whittle: Gait Analysis - an introduction 4th ed. Elsevier, 2007, pp. 80 ff.
  4. ↑ Chris Kirtley: Clinical Gait Analysis Elsevier, 2006. pp. 105 ff.
  5. ↑ Chris Kirtley: Clinical Gait Analysis Elsevier, 2006. P. 133 ff.
  6. ↑ Ge Gao, Maria Kyrarini, Mohammad Razavi, Xingchen Wang, Axel Gräser: Comparison of Dynamic Vision Sensor-Based and IMU-based systems for ankle joint angle gait analysis . In: 2016 2nd International Conference on Frontiers of Signal Processing (ICFSP) . October 2016, p. 93-98 , doi : 10.1109 / ICFSP.2016.7802963 ( ieee.org [accessed July 18, 2020]).
  7. ↑ Giulia Pacini Panebianco, Maria Cristina Bisi, Rita Stagni, Silvia Fantozzi: Analysis of the performance of 17 algorithms from a systematic review: Influence of sensor position, analyzed variable and computational approach in gait timing estimation from IMU measurements . In: Gait & Posture . tape 66 , October 1, 2018, ISSN  0966-6362 , p. 76–82 , doi : 10.1016 / j.gaitpost.2018.08.025 ( sciencedirect.com [accessed July 18, 2020]).
  8. ↑ Jung-Ah Lee, Sang-Hyun Cho, Young-Jae Lee, Heui-Kyung Yang, Jeong-Whan Lee: Portable Activity Monitoring System for Temporal Parameters of Gait Cycles . In: Journal of Medical Systems . tape 34 , no. 5 , October 1, 2010, ISSN  1573-689X , p. 959–966 , doi : 10.1007 / s10916-009-9311-8 (DOI = 10.1007 / s10916-009-9311-8 [accessed July 18, 2020]).
  9. ↑ Jens Barth, Cäcilia Oberndorfer, Cristian Pasluosta, Samuel Schülein, Heiko Gassner: Stride Segmentation during Free Walk Movements Using Multi-Dimensional Subsequence Dynamic Time Warping on Inertial Sensor Data . In: Sensors . tape 15 , no. 3 , 2015, p. 6419–6440 , doi : 10.3390 / s150306419 ( mdpi.com [accessed July 18, 2020]).
  10. ↑ Sebastijan Šprager, Matjaž B. Jurič: Robust Stride Segmentation of Inertial Signals Based on Local Cyclicity Estimation . In: Sensors . tape 18 , no. 4 , 2018, p. 1091 , doi : 10.3390 / s18041091 ( mdpi.com [accessed July 18, 2020]).
  11. ↑ Nooshin Haji Ghassemi, Julius Hannink, Christine F. Martindale, Heiko Gassner, Meinard Müller: Segmentation of Gait Sequences in Sensor-Based Movement Analysis: A Comparison of Methods in Parkinson's Disease . In: Sensors . tape 18 , no. 1 , 2018, p. 145 , doi : 10.3390 / s18010145 ( mdpi.com [accessed July 18, 2020]).
  12. ↑ J. Perry: Gait Analysis . Second Edition, Slack Incorporated, 2010.
  13. ↑ L. Döderlein, S. Wolf, 2004, The importance of instrumental gait analysis in infantile cerebral palsy. Der Orthopäde , Volume 33, No. 10, pp. 1103–1118, see p. 1106. Quoted from: Sangbok Moon, Investigation of balance and gait in patients with knee and hip endoprostheses , dissertation, Saarland University, 2014, p 98.
  14. ↑ Julius Hannink, Malte Ollenschläger, Felix Kluge, Nils Roth, Jochen Klucken: Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis . In: Sensors . tape 17 , no. 9 , 2017, p. 1940 , doi : 10.3390 / s17091940 ( mdpi.com [accessed July 18, 2020]).
  15. ↑ Ludwig, Oliver: Gait analysis in practice - application in prevention, therapy and care C. Maurer-Verlag, Geislingen, 2012, p. 10 ff.
  16. ↑ Alan Niederer: What the gait says about the risk of falling. In: NZZ. November 2, 2011, accessed October 10, 2018 .
  17. ↑ John W. Michael: Lower Limb Protheses: Implications and Applications, in: Jessica Rose, James G. Gamble: Human Walking, 1st ed., Lippincott Williams & Wilkins, 2006, pp. 185 ff.
  18. ↑ Ludwig, Oliver: Gait Analysis in Practice - Application in Prevention, Therapy and Care C. Maurer-Verlag, Geislingen, 2012, pp. 162–178.
  19. ↑ David H. Sutherland: The evolution of clinical gait analysis part I: Kinesiological EMG in: Gait and Posture 14 (2001). P. 61.
  20. ^ Braune, W., Fischer, O. (1889): About the center of gravity of the human body with regard to the equipment of the German infantryman. In: Treatises of the Royal Saxon Society of Sciences 15: 561–672.
  21. ↑ David H. Sutherland: The evolution of clinical gait analysis par tII: kinematics in: Gait and Posture '16 (200) p. 160.
  22. ^ David A. Winter The Biomechanics and Motor Control of Human Movement. Pp. 75-139, including a calculation example.