Gymnastik- och idrottshögskolan, GIH

Modifications in shoe outer soles are frequently made with the intention of altering biomechanics of the foot inside the shoe. These modifications are however, generally based upon intuition with little or no scientific data for support. The purpose of this study was to quantify changes in intrinsic foot segmental kinematics between walking in a neutral shoe and a shoe modified with a clear cut forming a break underneath the midfoot, approximating the Lisfrancs joint.

Five healthy male subjects participated in the study. Intracortical pins were inserted under sterile conditions and local anaesthetic in nine different bones of the foot and shank. The subjects performed 10 walking trials in both a neutral, standard, flatsoled, flexible walking shoe and in the same shoe with an approximately 1 cm deep cut aligned with the subjects’ Lisfrancs joint. Material tests showed that the cut reduced midfoot shoe bending stiffness by 23% to 38% and torsional stiffness by 23% to 28%. A helical axis approach was applied for calculating the 3D rotations about relevant joints.

Kinematic trajectories in the sagittal, frontal, and transverse planes were normalised to the stance phase for seven selected joints to compare rotation patterns when wearing the two shoe conditions. Although one out of 21 ranges of motion (ROM) showed a significant difference, there is strong reason to regard this as the result of a type 1 error. Apart from this no differences in ROM occurred between the shoe conditions.

The low subject number reduced the statistical power of the results. However, the study indicated that outer sole modifications that may be assumed to have clear effects upon foot kinematics, do not necessarily do so.

For all athletes, it is important to adjust training plans and competition schedule according to each individual's specific traits and situation. This is crucial in team sports, where players, despite being involved in the same sport, and even on the same team, may have very different physiological capacities and, also have completed a wide variety of work in both training and match situations. A first step towards being able to carry out individualized training is to accurately measure the amount of stress (physiological burden) for each individual. The purpose of the study was to create a comprehensive picture of the physical requirements of elite handball matches, and further investigate how the relationship between work load and physical capacity impacts performance.

Heart rate measurements have since decades been used to quantify the relative work, and GPS measurement as a tool for objective values has been available for outdoor sports for about ten years, but GPS is not possible to use indoors. We have used a new technology with a similar system for indoor use called Local Positioning System (LPS) (Kinexon Precision Technologies, Münich, Germany) to record and analyze the players’ motion during games, and we have combined that technology with data from accelerometry, gyroscope and heart rate measurements.

So far, 42 handball matches have been measured and analyzed, ranging from juniors (9 games U21 men's national team) to seniors, men and women, and both in Sweden’s highest league and between national teams (Women: 8 national and 7 international games; Men: 14 national and 4 international games).

A first "result" is that the categorization of motion patterns need to be adapted to each sport. For example, some moves that should be counted as accelerations in handball are not recognized by the system, simply because it has been adapted to the pattern of motion on the much larger soccer field. This is similarly important to realize when comparing results for handball’s physiological requirements reached using other technologies. In this presentation, we will in part discuss the future technological opportunities, and in part report descriptive results, including how fast and far the players move, as well as differences between men and women, between national and international games, and between juniors and seniors.

INTRODUCTION/PURPOSE:

The aim of this study was to describe the effect of an anti pronation foot orthosis on motion of the heel relative to the leg and explore the individual contributions of the ankle and subtalar joints to this effect.

METHODS:

Five subjects were investigated using invasive intracortical pins to track the movement of the tibia, talus and calcaneus during walking with and without a foot orthosis.

RESULTS:

The anti pronation foot orthosis produced small and unsystematic reductions in eversion and abduction of the heel relative to the leg at various times during stance. Changes in calcaneus-tibia motion were comparable to those described in the literature (1-3°). Changes at both the ankle and subtalar joints contributed to this orthotic effect. However, the nature and scale of changes was highly variable between subjects. Peak angular position, range of motion and angular velocity in frontal and transverse planes were affected to different degrees in different subjects. In some cases changes occurred mainly at the ankle, in other cases changes occurred mainly at the subtalar joint.

CONCLUSION:

The changes in ankle and subtalar kinematics in response to the foot orthosis contradict existing orthotic paradigms that assume that changes occur only at the subtalar joint. The kinematic changes due to the orthosis are indicative of a strong interaction between the often common function of the ankle and subtalar joints.

Background: The ability to measure activity and physiology through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. Objective: To assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. Methods: We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 +/- 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Results: Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. Conclusions: Most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).