Foot and Ankle Kinematics During Gait Using Foot ...

Foot and Ankle Kinematics During Gait Using Foot Mounted Inertial System S.P. Kwakkel, S. Godha, and G. Lachapelle Positioning Location and Navigation Group (PLAN) Department of Geomatics Engineering, Schulich School of Engineering University of Calgary, Calgary, Alberta, Canada BIOGRAPHY Mr. Sidney Kwakkel is an undergraduate student from the department of Geomatics Engineering with a specialization in Biomedical Engineering at the University of Calgary. He holds a BSc in Biological Sciences from the University of Calgary. His current research is focused on kinematic analysis of human movement using inertial sensors. Mr. Saurabh Godha is a Research Engineer in the PLAN Group and he holds an MSc from the Department of Geomatics Engineering, at the University of Calgary. He completed his B.Tech in Civil Engineering from the Indian Institute of Technology (IIT), Bombay. His current research is focused on integrated IMU/GPS navigation systems for pedestrian and vehicular navigation. Dr. Gérard Lachapelle is a Professor of Geomatics Engineering at the University of Calgary where he is responsible for teaching and research related to location, positioning, and navigation. He has been involved with GPS developments and applications since 1980. He has held a Canada Research Chair/iCORE Chair in wireless location since 2001 and heads the PLAN Group at the University of Calgary. See http://PLAN.geomatics.ucalgary.ca for details. ABSTRACT This paper evaluates the performance of field-portable, low cost IMUs for the kinematic analysis of foot/ankle rotations. Three MEMS-based IMU sensors are attached to the left leg of test subjects, who were then asked to walk a flat ground course of 40 m. A global averaged gait profile including five individuals was computed using stride detection algorithms, while IMU drift errors were mitigated by Zero Velocity Updates (ZUPTs) made during the stance phase. The results were compared against those of a landmark study in foot and ankle kinematics. In a single case, an individual was asked to walk a 40 m straight-line course uphill with a 9% grade. A comparison is made between this individual’s flatground and hill gait profile, and the results are again compared to published literature. In both cases, flat

ION NTM 2007, San Diego CA, 22-24 January 2007

ground and hill, the results provided by IMU-based kinematic analysis of the foot/ankle were very promising and will lead to more research in this area. INTRODUCTION Foot and ankle kinematics have long been an interesting topic in the realm of human motion analysis. Since Da Vinci (1452-1519) sought to describe the mechanics of everyday movements in the 15th century, and then Borelli (1608-1679) elucidated the equilibrium forces in human joints, science has had a keen interest in quantifying the movement within the foot/ankle complex. More contemporary interests in foot/ankle kinematic analysis include the clinical diagnosis of diseases such as Parkinson’s (Salarian et al 2004) and Huntington’s (Hausdorff 1998), as well as everyday conditions such as lower back pain (Dananberg 1993), old age (Gabell and Nayak 1984) and a variety of other common applications (Reischl et al 1999, Buckon et al 2001, Powers et al 2002). The important quantities to review in a kinematic description of the foot/ankle are the rotations in the coronal and sagittal planes (see Figure 1). The rotations in the sagittal plane are commonly termed dorsiflexion (toeup) and plantarflexion (toe-down), whereas in the coronal plane inversion (internal rotation) and eversion (external rotation) are the commonly used terms. In addition to these, complex rotations such as the inward (medial) roll of the foot over a gait cycle, termed pronation, and the outward (lateral) rotation movement, termed supination, are important quantities of interest because they are used in the diagnosis of disease. For instance, over-pronation – a condition where the individual’s foot rolls too far inward – is the cause of many acute and chronic lower limb musculoskeletal pathologies and injuries (Powers et al 2002, Landorf 2003). To date, there has been very little work to study the pronation and supination of the ankle/foot and thus, their kinematics and kinetics are not very well understood (Nigg 2001). Thus, the specific objective of this paper is to devise field-portable methodologies and to propose a system to be able to analyze and quantify the pronation and supination profiles.

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Figure 1 – Depictions of kinematic orientation of the foot/ankle. Coronal plane: (a)Normal stance. (b) eversion. (c) inversion. Sagittal plane: (d) Normal stance. (e) dorsiflexion. (f) plantarflexion. The foot and ankle are made up of many joints (see Figure 2) that help absorb impact forces, keep the leg from incurring injury-causing stresses, and most importantly, allow for locomotion. Three joints, namely the subtalar joint, calcanocuboid joint and taleonavicular joint, are primarily responsible for pronation and supination. The subtalar joint is the joint joining the lower limb (shank) with the foot, while the other two separate the rearfoot and forefoot. These joints allow for the complex movement of the foot and ankle and result in many subtle forces and rotations in all three axes. The organic components (i.e. ligaments and surrounding musculature) of these joints are responsible for interindividual differences in pronation/supination, but these kinetics are left for other studies. For this study, the

Figure 2 – Joints of the lower limb ankle and foot. The subtalar joint formed between the talus and calcaneus. The calcanocuboid joint and the taleonavicular joint.

ION NTM 2007, San Diego CA, 22-24 January 2007

Figure 3 – Modified representation of the segments of the foot and ankle complex as defined by Kidder et al (1996). Shank (tibia and fibula), rearfoot (calcaneus, talus, and navicular), forefoot (cuneiforms, cuboid and metatarsals) and the big toe (hallux). kinematics of these joints is of interest. The ability to measure the rotations between the segments of the foot and ankle is important because they reflect the underlying joint kinematics. This is an important first step for the study of pronation/supination profile and possibly the clinical remediation of conditions such as over-pronation or the diagnosis of degenerative diseases such as Parkinson’s or Huntington’s. Current methods of analyzing such motions involve the use of commercial optical systems such as Vicon® (reflective) and Optitrak® (active), which are considered the ‘gold standard’ in this arena. The appeal of out-of-thebox solutions that come with easy-to-use software and expert technical support is understandable in a multidisciplinary field such as human motion analysis. However, this method suffers from some drawbacks that limit its usefulness. The most important factors are the high costs and limited measurement volume. For instance, camera systems often require elaborate dedicated lab space, but subjects can only be measured within the scope of these setups. This constraint makes long range in-situ measurements difficult without the use of a treadmill, which does not accurately reflect the subject’s everyday environment. This is an important consideration in assessing pronation in long-range applications such as in runners (Hintermann & Nigg 1998) or in-situ analysis of subjects during everyday activities. Despite these limitations, the traditional approach to foot and ankle kinematics is through these methods. A landmark study, Kidder et al (1996), described a method of optical marker placement that was instrumental in observing the various segments of the foot and ankle

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complex (see Figure 3). The four foot model segments, as described in the Kidder study, were the shank (tibia and fibula), rearfoot (calcaneus, talus, and navicular), forefoot (cuneiforms, cuboid and metatarsals) and the big toe (hallux). The markers were placed to isolate each segment to allow rotations around three axes to be determined for each segment in relation to the subsequent segment. In designing the metrics to be used in this study, consistency with this framework was a priority so that newly gathered information could be critically assessed with past knowledge. Another study performed by Lay et al (2006) measured ankle flexion (sagittal plane rotations between the shank and rearfoot) as a function of the grade of the walking surface. While the rotations between other segments and rotations in other planes were ignored in the Lay study, it provides a reference for foot/ankle kinematics for individuals walking on hills. MEMS IMU & SENSOR PLACEMENT

Figure 4 – Crista IMU. Image from Godha et al (2006).

The availability of low cost Micro Electro-Mechanical System (MEMS) inertial measurement units (IMU) has allowed for promising developments in

foot mounted pedestrian navigation systems (e.g. Lachapelle et al 2005, Godha et al 2006). These studies employ a single foot mounted IMU and are able to measure triaxial accelerations and rotations during gait; the latter, specifically roll and pitch rotations, being the quantities needed for foot/ankle kinematic analysis. For the clinical application of an inertial kinematic analysis system there are many factors than must be considered. Firstly, the sensor must interfere as little as possible with the gait of the test subject. This requires that weight and dimensions of the sensor be of paramount considerations. Secondly, the level of precision of the sensor must be adequate to measure the desired movement. For this study, the Crista MEMS IMU by Cloud Cap Technology (Figure 4) is used. The reasons are twofold: the unit is lightweight and small (Table 1) so it will not alter the individual’s gait. However, the in-run biases of this particular IMU would not allow for precise enough measurements to obtain the desired quantities (i.e. pitch and roll). A method for mitigating these errors is needed and will be discussed further in this paper. The current state of MEMS IMU technology combined with certain processing algorithms have been shown by Godha et al (2006) to improve the quality of measurement, especially in coronal and sagittal planes. Moreover, as MEMS technology becomes better over time these concerns will become less of an issue. A second, and equally important factor in the design of this system will be the placement of sensors. Given that the relative angles between the segments of the lower

Table 1 – Physical specifications of the Crista IMU by Cloud Cap Technologies (Crista-Interface/ Operation Document 2005) Weight* (gm) 37 Size* (cm) 5.2 x 3.9 x 2.5 Accelerometers In run bias (mg) Turn on bias (mg) Scale factor (PPM) Velocity random walk (g/√Hz)

2.5 30 10 000 370e-006**

Gyros In run bias (°/hr) Turn on bias (°/hr) Scale factor (PPM) Velocity random walk (°/hr /√Hz)