Secondary Logo

Journal Logo

Section Articles

Methods of Running Gait Analysis

Higginson, Brian K.

Author Information
Current Sports Medicine Reports: May 2009 - Volume 8 - Issue 3 - p 136-141
doi: 10.1249/JSR.0b013e3181a6187a
  • Free



As running continues to grow in popularity, so does the interest in research and assessment of running gait. Recent advancement and proliferation of technology used in the analysis of running gait is making this capability more widely available to a broader range of professionals. No longer is running gait analysis limited to the well-funded clinical gait analysis and research labs. One has only to attend a major running event, such as the Boston marathon, to witness firsthand the use of technology capable of providing immediate feedback on rearfoot motion during running and quantitative analysis of arch structure, used to prescribe the most ideal running shoe for an individual. Perhaps more important than the availability of such systems is their utility. Data collection equipment used for the analysis of running gait continues to get smaller, more affordable, and portable, and such data collection no longer is constrained to research or clinical settings.

In-depth reviews upon the biomechanics of running gait have been presented elsewhere (8,15,27,35,50) and are beyond the scope of this paper. These reviews provide an introduction to the basic biomechanics of running, including anatomical considerations of the foot and normal foot motion during walking and running. Also included are common measures of interest in the analysis of running gait and how these measures change as a function of gait cycle and running speed.

The dramatic increase in the number of recreational and competitive runners in recent years has obvious implications to professionals such as clinicians, physical therapists, and coaches who offer services aimed at the evaluation and rehabilitation of running-related injuries and performance enhancement strategies. Recent technological advancements now facilitate a greater range of individuals able to provide these services. With more becoming known about the mechanisms of injury, clinicians may become more involved in the prevention and rehabilitation of running-related injuries. With this increased demand comes an increase in the need to be knowledgeable of the technology currently available to provide these services. Therefore, this review is intended as a brief overview of the current technologies used in the assessment of running gait, with a focus upon the latest developments and equipment.

Many tools have been developed to assist in the assessment of running gait. These include the more traditional motion capture systems used to describe motion of the body, force plates that quantify the forces acting on the body, and electromyography (EMG) used to estimate the level of muscle activity during motion. More recently, smaller portable sensors have been developed and successfully used to measure running gait parameters. These include accelerometers, electrogoniometers, gyroscopes, and in-sole pressure sensors. These tools have been successfully used to investigate shoe (5,9,14,34,47) and orthotic (30,31) performance, risk factors for injury (29), running performance (45,46), fatigue effects (13,23), and gait adaptations to various running techniques (19). For a summary of the specific gait parameters measured by each system and sensor, refer to the Table.

Summary of running gait parameters measured by each sensor or system.

Motion Analysis

Gait analysis often requires the quantification of motion of individual body segments in two- or three-dimensional space. The most common method for collecting this information is through the use of motion capture technology, in which markers are affixed to the subject and tracked throughout the motion of interest. These systems typically use passive markers that reflect ambient or infrared light, active markers that emit light (light-emitting diodes), or electromagnetic systems that are able to detect the position and orientation of the receiver placed on a body segment relative to an externally fixed transmitter. Through manual or automatic digitization techniques, the coordinate location (two- or three-dimensional) of the markers can be determined. From these position data, the velocity and acceleration can then be calculated by taking the time derivative of the position and velocity, respectively.

Direct comparisons made between optical and electromagnetic systems indicate that measurements obtained from either system are comparable and accurate (17). However, each system does have its limitations. Optical systems are prone to marker occlusion if there exists a significant number of markers or an insufficient number of cameras. Electromagnetic systems are susceptible to magnetic interference from metal objects located within or near the capture volume (28), and their accuracy is affected by the distance between the transmitter and receivers (50). Limitations inherent in both systems include the need of skilled operators and the fact that they can be prohibitively expensive, have a relatively small capture volume, and require a controlled environment in which to operate (43). Edge detection technology recently has shown promise in allowing gait parameters to be quantified directly from video sources alone (44), allowing the same information to be extracted as that from marker-based systems, without the associated limitations or need for markers.

Although treadmills often are used in the analysis of walking and running gait to overcome issues surrounding small capture volumes, their use is believed to induce gait adaptations, such as increased time in stance phase, that normally would not be observed in overground running (15). These changes appear to be speed dependent, with walking speed eliciting little or no change in gait patterns (41), while changes in running gait appear to be determined more by the individual subject's running style, running speed, and shoe/treadmill interaction (33). Protocols used for the analysis of running gait typically incorporate a treadmill familiarization period (19) to minimize the potential changes in gait across running modes and may be of particular importance when considering treadmill naïve runners (33). Because of the amount of metal components used in the construction of commercially available treadmills, there exist obvious implications when used in combination with electromagnetic motion tracking systems. However, treadmill modifications have been successfully used to facilitate their use with these systems (28).

Force Analysis

Force plates commonly are used to measure contact forces between the foot and ground during the stance phase of gait. This information can be used to quantify impact forces, loading rates, and propulsive and breaking forces, and track changes in the center of pressure (CoP) over time. Because of their relatively small size, however, they impose constraints on foot placement, which may result in subjects adopting a "targeting" strategy while running, altering natural gait mechanics (37). This targeting strategy can lead to increased step length variability (49) and often results in exclusion of the trial (29), resulting in prolonged data collection periods and subject fatigue. Although the influence of targeting shows little effect upon ground reaction forces during walking gait (49), greater approach velocities associated with running and larger changes in relative stride length to contact the force platform may result in more significant differences observed in ground reaction forces at these higher speeds.

Recently, the development of instrumented treadmills have allowed for the quick collection of ground reaction forces over repeated gait cycles, allowing for highly controlled gait speed, while eliminating potential error introduced by targeting strategies. Many designs have been used in the development of instrumented treadmills, including mounting the treadmill to force transducers embedded in the ground or mounting force plates under the belt surface (3,11,12). Instrumented treadmills using multiple force plates have been used primarily to address issues regarding the summation of forces from both feet during the double support phase of walking. Because running is defined by its single support and flight phases, all measured forces are representative of the loads under a single foot (10), allowing analysis to be performed using the single force plate design. Although instrumented treadmills have been used to accurately measure ground reaction forces during running, treadmills using force plates beneath the belt can be susceptible to noise because of friction of the belt moving over the plate. However, this noise is limited primarily to the direction of belt travel and has relatively little influence upon vertical or medial/lateral force measurements (37).


The use of in-shoe pressure sensors provides a lightweight, portable, and easy-to-use alternative in which to analyze running gait. Unlike force platforms, they are capable of quantifying the distribution of force over the plantar surface of the foot, providing more detailed information on the loading of the foot during gait than force measures alone. Because this device is placed in the shoe, the loads acting on the foot surface are able to be measured directly, as opposed to the force acting on the bottom of the shoe with a standard force platform (14). For this reason, in-shoe pressure sensors commonly are used to quantify the effect of shoe design upon foot loading and have been used to compare loading of the foot between similar shoe types (9) and between shoes of different midsole designs (14), as well as changes in the impact absorbing capabilities of a shoe over repeated impact cycles (47).

In-shoe pressure sensors also provide the ability to measure vertical forces experienced by the foot during prolonged running (19) and detect typical gait parameters required for gait analysis, such as heel strike and toe-off needed to define the stance phase of gait (7). Although force platforms are considered to be the gold standard method by which these measurements typically are collected, as mentioned previously, they are limited in the number of steps able to be sampled and typically are restricted to use in a laboratory setting. In-shoe pressure sensors give the researcher or clinician the flexibility to collect data from repeated foot strikes in an environment that facilitates normal running gait.

Plantar loading parameters obtained from in-shoe pressure sensors have shown high reliability across multiple trials of the same subject, with low variability between steps (32), and are repeatable between testing days (40). Analysis of ground reaction force parameters indicates that these measures also are reliable over a range of running speeds and stride frequencies (19) when collected using pressure sensors. However, comparison of the two most popular in-shoe pressure measurement systems indicates that the accuracy and precision of these systems may be sensitive to the levels of pressure applied, calibration procedure, duration of pressure application, and insole age of use (18).


Electromyography (EMG) is a technique commonly used to measure levels of muscle activity during walking or running gait. Typically, timing of muscle activation and relative intensity are the primary measures of interest and can be collected through the use of surface or indwelling (fine-wire) electrodes. This technique can be used to detect abnormal gait behavior and assess the neuromuscular control of a runner (15). Normal muscle activation during the stride and stance phases of running (8,35) and sprinting (27) have been reported elsewhere, as well as how muscle activation and timing patterns are influenced by changes in walking and running speeds (6).

In addition to providing information about muscle activation levels and timing, the frequency content of the EMG signal can be analyzed to determine relative muscle fatigue (48), which may be used in the early detection of potential running injuries. There also are data to suggest that EMG parameters may be a more sensitive measure than force measures in explaining differences in shoe/orthotic comfort ratings (30). EMG parameters have been found to be highly reproducible between gait cycles when compared across different running techniques (running velocity and stride frequency), but tend to be less reproducible when compared across individual muscles, with distal leg muscles showing more reproducibility than proximal leg muscles during running (19). Depending upon the particular muscle of interest, this information may influence selection of gait analysis protocols by decreasing (or increasing) the number of stride cycles needing to be analyzed.

One major drawback of older EMG systems is that data were transmitted via cable, potentially limiting the motion of the subject. Newer systems incorporate technology that allow for the data to be transmitted wirelessly or stored in a data logger worn by the subject, vastly increasing the functionality of these systems. Other limitations include crosstalk between muscles and electrical noise from external sources (16). The incorporation of in-line preamplification devices has greatly reduced ambient noise in the underlying myographic signal (44), allowing for greater signal-to-noise ratio. Although selection of appropriate signal processing and normalization techniques, selection of muscle onset-offset determination algorithms, and data interpretation may seem a rather daunting task to the uninitiated, many current systems are designed to accommodate various levels of user proficiency.


The use of body-fixed sensors such as accelerometers rapidly are becoming a viable alternative to more traditional gait analysis techniques for use in the assessment of human motion. Accelerometers are inertial sensors that provide a direct measurement of acceleration along single or multiple axes, effectively reducing the error associated with differentiation of displacement and velocity data derived from sources such as motion capture systems. Accelerometer-based systems have been used successfully to quantify the shock experienced by the lower extremity during walking and running (5,22,29), evaluate the effect of footwear (5) and insoles (36) upon tibial shock during running, evaluate shock attenuation between body segments during running (26), and investigate the effects of fatigue upon running gait patterns (23).

The ability of some accelerometers to respond to both gravitational acceleration as well as acceleration caused by movement also allows them to be used for the measurement of segment orientation under static conditions (20). The utility of accelerometers in gait analysis can be enhanced further through the concurrent use of gyroscopes and electrogoniometers (described later). Accelerometers, when combined with rate gyroscopes, have been found to produce similar joint angle, angular velocity, and angular acceleration derived from motion capture systems under dynamic conditions (25), and effectively have been used to estimate walking speed and surface inclination angles (43).

Perhaps the most appealing advantage is the ability of accelerometers to be used in the estimation of spatiotemporal gait parameters (43), which until recently required the use of a force plate, motion analysis systems, or footswitches. As addressed in previous sections, a primary limitation of motion capture systems and force plates in the analysis of running gait is their limited ability to measure successive strides. Because of their light weight and portability, accelerometers are capable of recording data that can be collected continuously over many stride cycles for a prolonged period of time. This technology has been used effectively to detect alterations in running patterns after the onset of fatigue in middle-distance runners while running on a track, without altering the running patterns of the runner (23).

Although mechanical testing has confirmed the validity and reliability of accelerometers in the measurement of accelerations within the frequency and amplitude range of human body motion (4), evidence indicates that they are sensitive to the site and method of attachment, with skin-mounted accelerometers resulting in significantly greater peak accelerations than bone mounted accelerometers (21). However, direct comparison of axial acceleration of the tibia during running found that the disparity in results between attachment methods to be largely subject dependent (22). That being said, while skin-mounted accelerometers are known to overestimate peak tibial acceleration in some subjects, the alternative attachment method may not be an appealing, or feasible, option for most. Regardless of the limitations associated with skin-mounted accelerometers, they have been used successfully to distinguish between runners with previous history of tibial stress fractures and asymptomatic runners (29). For a comprehensive review of current accelerometer technology used in the evaluation of gait patterns, see Kavanagh and Menz (20).


Electrogoniometers allow for the direct measurement of joint angles during continuous dynamic activities. They offer a simple, affordable alternative to motion capture systems and allow joint angle data to be collected and viewed instantaneously. The end blocks of the electrogoniometers typically are affixed to the skin on either side of the joint axis of rotation using double-sided adhesive tape, as specified by the manufacturer. This method has been found to result in excess sensor motion (42), which potentially could be magnified during the high-speed changes in joint angle commonly experienced during running. This unwanted sensor motion effectively can be reduced through the use of additional adhesive tape (39) or application of pre-wrap and athletic tape (13). For prolonged periods of data collection, special suits have been fabricated, which facilitates attachment of the electrogoniometers using hook and loop fasteners (38). Failure to prevent sensor motion and improper alignment of the sensor during the application procedure has been found to be the greatest potential contributor to measurement error (39,42,51).

Measurement error from electrogoniometers has been shown to be as small as 0.04 degrees (39) and has been validated using both human (42) and mechanical (39) testing protocols, with results comparable to those obtained using motion capture systems (42). Although studies have shown inter- and intra-tester reliability to be relatively high, it has been suggested that the same tester be used when possible to ensure the highest repeatability (39).

These measurement devices have been found to be extremely robust when exposed to environmental factors such as heat shock and electrical noise (42). When applied correctly, electrogoniometers have proven to be highly accurate and highly sensitive for detecting changes in joint angles over time, providing a simple, small, portable, and affordable alternative to motion capture systems.


Gyroscopes are miniature angular rate sensors that can be attached to individual body segments, providing a direct measure of segment angular velocity. Angular orientation can then be calculated by integration of the angular velocity data. This sensing technology has been found to be an inexpensive alternative to motion analysis systems (25), and methods recently have been developed to calculate spatiotemporal gait parameters based upon the angular velocity measures provided by these sensors (1,43). Calculation of the spatiotemporal gait parameters using these methods shows little measurement error when compared with direct measurement using foot pressure sensors (1).

In addition to allowing the direct measurement of segmental angular velocity and orientation, and calculation of spatiotemporal gait parameters, other benefits of using gyroscopes include their small size and portability, lower power requirement (51), ease of attachment compared with accelerometers, and insensitivity to gravitation influence (43). As with accelerometers and marker-based motion capture systems, signal integrity is compromised by unwanted sensor motion resulting from poor fixation or site selection.


Although traditional methods used in the analysis of running gait, such as motion capture systems and force plates, have been used widely in the analysis of walking and running gait, they are not without their limitations. Recent advancements in technology have allowed for the development of sensors such as electrogoniometers, accelerometers, gyroscopes, and in-shoe pressure sensors. These sensors offer a lightweight, portable, and inexpensive alternative to motion analysis systems and force platforms. Combined with technology such as telemetry and data loggers, they allow data collection during unconstrained continuous movement over prolonged periods of time. This makes data collection feasible during activities such as outdoor running and potentially even can be used during training and competition.

These technological advancements, along with new information regarding mechanisms of running-related injuries and prevention and rehabilitation strategies, may increase the number of running gait analyses performed by the clinician. This technology also serves to broaden the scope of application, allowing even coaches and runners access to information never before possible, enabling them to make more informed decisions regarding the influence of running mechanics upon performance or injury.

Along with the portability and utility afforded by these new sensors, they provide an opportunity for users to fabricate equipment specific to their needs and applications. No longer must they rely on "all-up" data acquisition systems supplied by manufacturers with limited capability or expandability. It has become increasingly common for researchers to fabricate custom measurement devices using various combinations of these sensor technologies. Although no commercially available "gait shoe" exists, there have been those who have had success in manufacturing or modifying shoes to accurately measure ground reaction forces and center of pressure (24), as well as foot motion and spatiotemporal gait parameters (2). Although the "gait shoe" proposed by Bamberg (2) consisted of a "sensor suite" including a total of 15 sensors (three accelerometers, three gyroscopes, four force transducers, two bidirectional bend sensors, two pressure sensors, and electric field height sensor), the total cost was less than $500 and weighed less than 300 g.

The future in gait assessment seems obvious. With prototype "gait shoes" incorporating multiple sensors into a single shoe that are lightweight, don't hinder the natural motion of the wearer, yet are able to detect motion, force, and pressure data, it seems a matter of time before this technology is refined to the point where it is commercially available. Because of competition and continued technological advances, it is expected that these types of gait analysis systems will become more prolific and affordable in the near future.


1. Aminian K, Najafi B, Bula C, Leyvraz PF, Robert P. Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. J. Biomech. 2002; 35:689-99.
2. Bamberg SJM, Benbasat AY, Scarborough DM, Krebs DE, Paradiso JA. Gait analysis using a shoe-integrated wireless sensor system. IEEE Trans. Tech. Biomed. 2008; 12(4):413-23.
3. Belli A, Bui P, Berger A, Geyssant A, Lacour JR. A treadmill ergometer for three-dimensional ground reaction forces measurement during walking. J. Biomech. 2001; 34:105-12.
4. Bouten CVC, Koekkoek KTM, Verduin M, Kodde R, Janssen JD. A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity. IEEE Trans. Biomed. Eng. 1997; 44(3):136-47.
5. Butler RJ, Davis IS, Hamill J. Interaction of arch type and footwear on running mechanics. Amer. J. Sports Med. 2006; 34(12):1998-2005.
6. Cappellini G, Ivanenko YP, Poppele RE, Lacquaniti F. Motor patterns in human walking and running. J. Neurophysiol. 2006; 95:3426-37.
7. Catalfamo P, Moser D, Ghoussayni S, Ewins D. Detection of gait events using an F-scan in-shoe pressure measurement system. Gait Post. 2008;28:420-6.
8. Cavanagh PR. Biomechanics of distance running. Champaign: Human Kinetics: 1990.
9. Clinghan R, Arnold GP, Drew TS, Cochrane LA, Abboud RJ. Do you get value for money when you buy an expensive pair of running shoes? Br. J. Sports Med. 2008; 42:189-93.
10. Davis BL, Cavanagh PR. Decomposition of superimposed ground reaction forces into left and right profiles. J. Biomech. 1993; 26(4-5):593-7.
11. Dierick F, Penta M, Renaut D, Detrembleur C. A force measuring treadmill in clinical gait analysis. Gait Post. 2004; 20:299-303.
12. Divert C, Morniex G, Baur H, Mayer F, Belli A. Mechanical comparison of barefoot and shod running. Int. J. Sports Med. 2005; 26:593-8.
13. Derrick TR, Dereu D, Mclean SP. Impacts and kinematic adjustments during an exhaustive run. Med. Sci. Sports Exerc. 2002; 34(6):998-1002.
14. Dixon SJ. Use of pressure insoles to compare in-shoe loading for modern running shoes. Ergonomics. 2008; 51(10):1503-14.
15. Dugan SA, Bhat KP. Biomechanics and analysis of running gait. Phys. Med. Rehabil. Clin. N. Am. 2005; 16:603-21.
16. Harris GF, Wertsch JJ. Procedures for gait analysis. Arch. Phys. Med. Rehabil. 1994; 75:216-25.
17. Hassan EA, Jenkyn TR, Dunning CE. Direct comparison of kinematic data collected using an electromagnetic tracking system versus a digital optical system. J. Biomech. 2007; 40:930-5.
18. Hsiao H, Guan J, Weatherly M. Accuracy and precision of two in-shoe pressure measurement systems. Ergonomics. 2002; 45(8):537-55.
19. Karamanidis K, Aramantios A, Bruggemann GP. Reproducibility of electromyography and ground reaction force during various running techniques. Gait Post. 2004; 19:115-23.
20. Kavanagh JJ, Menz HB. Accelerometry: A technique for quantifying movement patterns during walking. Gait Post. 2008; 28:1-15.
21. Lafortune MA. Three-dimensional acceleration of the tibia during walking and running. J. Biomech. 1991; 24(10):877-86.
22. Lafortune MA, Henning E, Valiant GA. Tibial shock measured with bone and skin mounted transducers. J. Biomech. 1995; 28(8):989-93.
23. Le Bris R, Billat V, Auvinet B, Chaleil D, Hamard L, Barrey E. Effect of fatique on stride pattern continuously measured by an accelerometric gait recorder in middle distance runners. J. Sports Med. Phys. Fitness. 2006; 46:227-31.
24. Liedtke C, Fokkenrood SAW, Menger JT, van der Kooij H, Veltink PH. Evaluation of instrumented shoes for ambulatory assessment of ground reaction forces. Gait Post. 2007; 26:39-47.
25. Mayagoitia RE, Nene AV, Veltink PH. Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. J. Biomech. 2002; 35:537-42.
26. Mercer JA, Bates BT, Dufek JS, Hreljak A. Characteristics of shock attenuation during fatigued running. J. Sports Sci. 2003; 21:911-9.
27. Mero A, Komi PV, Gregor RJ. Biomechanics of sprint running. Sports. Med. 1992; 13(6):376-92.
28. Mills PM, Morrison S, Lloyd DG, Barrett RS. Repeatability of 3D gait kinematics obtained from an electromagnetic tracking system during treadmill locomotion. J. Biomech. 2007; 40:1504-11.
29. Milner CE, Ferber R, Pollard CD, Hamill J, Davis IS. Biomechanical factors associated with tibial stress fracture in female runners. Med. Sci. Sports. Exerc. 2005; 38(2):323-8.
30. Mundermann A, Nigg BM, Humble RN, Stefanyshyn DJ. Orthotic comfort is related to kinematics, kinetics, and EMG in recreational runners. Med. Sci. Sports Exerc. 2003; 35(10):1710-9.
31. Mundermann A, Wakeling JM, Nigg BM, Humble RN, Stefanyshyn DJ. Foot orthoses affect frequency components of muscle activity in the lower extremity. Gait Post. 2006; 23:295-302.
32. Murphy DF, Beynnon BD, Michelson JD, Vacek PM. Efficacy of plantar loading parameters during gait in terms of reliability, variability, effect of gender and relationship between contact area and plantar pressure. Foot Ank. Int. 2005; 26(2):171-9.
33. Nigg BM, DeBoer RW, Fisher V. A kinematic comparison of overground and treadmill running. Med. Sci. Sports Exerc. 1995; 27(1):98-105.
34. Nigg BM, Morlock M. The influence of lateral heel flare of running shoes on pronation and impact forces. Med. Sci. Sports Exerc. 1987; 19(3):294-302.
    35. Novacheck TF. The biomechanics of running. Gait Post. 1998; 7:77-95.
    36. O'Leary K, Vorpahl KA, Heiderscheit B. Effect of cushioned insoles on impact forces during running. J. Amer. Pod. Med. Assoc. 2008; 98(1):36-41.
    37. Paolini G, Croce UD, Riley PO, Newton FK, Kerrigan DC. Testing of a tri-instrumented-treadmill unit for kinetic analysis of locomotion tasks in static and dynamic loading conditions. Med. Eng. Phys. 2007;29:404-11.
    38. Pierre MC, Genc KO, Litow M, Humphreys B, Rice AJ, Maender CC, Cavanagh PR. Comparison of knee motion on Earth and in space: an observational study. J. Neuro. Rehab. 2006; 3(8):1-8.
    39. Piriyaprasarth P, Morris ME, Winter A, Bialocerkowski AE. The reliability of knee joint position testing using electrogoniometry. BMC Muscul. Disord. 2008; 9(6):1-10.
    40. Putti AB, Arnold GP, Cochrane L, Abboud RJ. The Pedar in-shoe system: repeatability and normal pressure values. Gait Post. 2007; 25:401-5.
    41. Riley PO, Paolini G, Croce UD, Paylo KW, Kerrigan DC. A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects. Gait Post. 2007; 26:17-24.
    42. Rowe PJ, Myles CM, Hillman SJ, Hazelwood ME. Validation of flexible electrogoniometry as a measure of joint kinematics. Physiotherapy. 2001; 87(9):479-88.
    43. Sabatini AM, Martelloni C, Scapellato S, Cavallo F. Assessment of walking features from foot inertial sensing. IEEE Trans. Biomed. Eng. 2005; 52(3):486-94.
    44. Simon SR. Quantification of human motion: gait analysis-benefits and limitations to its application to clinical problems. J. Biomech. 2004; 37:1869-80.
    45. Stafilidis S, Arampatzis A. Track compliance does not affect sprinting performance. J. Sports Sci. 2007; 25(13):1479-90.
    46. Stefanyshyn D, Fusco C. Increased shoe bending stiffness increases sprint performance. Sports Biomech. 2004; 3(1):55-66.
    47. Verdejo R, Mills NJ. Heel-shoe interaction and the durability of EVA foam running-shoe midsole. J. Biomech. 2004; 37:1379-86.
    48. Wakeling JM, Pascual SA, Nigg BM, von Tscharner V. Surface EMG shows distinct populations of muscle activity when measured during sustained sub-maximal exercise. Eur. J. Appl. Physiol. 2001;86:40-7.
    49. Wearing SC, Urry SR, Smeathers JE. The effect of visual targeting on ground reaction force and temporospatial parameters of gait. Clin. Biomech. 2000; 15:583-91.
    50. Williams KR. Biomechanics of Running. Exer. Sport Sci. Rev. 1985; 13:389-421.
    51. Wong WY, Wong MS, Lo KH. Clinical applications of sensors for human posture and movement analysis: A review. Prosth. Orth. Int. 2007; 31(1):62-75.
    © 2009 American College of Sports Medicine