Measuring Pressure in Different Layers of the Ski Boot to

Estimate Skiing Movements

Aljoscha Hermann

, Patrick Carqueville

, Melanie Baldinger

and Veit Senner

Professorship of Sport Equipment and Materials, School of Engineering and Design,

Technical University of Munich, Munich, Germany

Keywords: Pressure Sensors, Measurement Boot, Measurement Sock, Alpine Skiing.

Abstract: A pressure sensing measurement ski boot or sock would allow to estimate body positions, skiing manoeuvres,

and external loads on the foot. This information may be used for research, in consumer products or for

intelligent safety systems like a mechatronic ski binding. To investigate the optimal placement of pressure

sensors with respect to the foot and the number of sensors needed to detect six pre-defined loading conditions,

three pressure sensor systems were developed measuring the pressure in three respective layers: between foot

and sock, sock and liner, liner and shell. The prototypes were evaluated in a laboratory test. The participant

performed a series of six simulated ski manoeuvres each held for 5 seconds. In this pilot test the system sock

/ liner shows the best overall performance due to pressure curves in the mid-range of the sensor characteristics.

Though, with an optimized sensor design a measurement boot with sensors between inner boot and shell may

be possible, which would increase the robustness of the system needed for a future customer product. As a

result of this study, a recommendation for sensor positions for the determination of the loading conditions in

alpine skiing is given.

1 INTRODUCTION

Tracking skiing loads is normally done with specially

developed equipment. An optimal sensor system

would not only allow to measure forces, but also to

calculate the resulting torques at the binding, the force

application points and the centre of gravity. This

information also allows to make assumptions about

the body position (for example a possible backward-

lean) and resulting loads at the knee (e.g. valgus/varus

due to a high side-load on the ski).

The use of standard laboratory dynamometers is

not applicable, as the system must be carried by the

skier or attached to the skiing equipment.

Several custom-made systems were developed for

recording the forces and moments acting on the ski.

Most systems are based on strain gauge sensors for

measuring the forces between the ski and the ski

binding or between the ski binding and the ski boot.

In many systems, forces and moments are recorded

https://orcid.org/0000-0003-3168-3273

https://orcid.org/0000-0001-7066-5225

https://orcid.org/0000-0002-5753-4025

https://orcid.org/0000-0001-5136-7580

separately for the front and back component of the ski

binding (Schwameder et al. 2001; Falda-Buscaiot et

al. 2017; Saito et al. 2015; Stricker et al. 2010). This

is advantageous if the force transmission through the

two binding components is investigated, but

susceptible for provoking and recording coercive

forces in the ski-boot-binding-complex, as the system

is statically overdetermined, thus limiting

interpretability of the results. Other systems use only

one sensing component (Kiefmann et al. 2006), thus

measuring the absolute skiing loads.

Such “measurement bindings” can give highly

accurate information about the forces, moments, and

the centre of vertical force application along the

longitudinal axis of the ski. On the other hand, these

bindings are unhandy to use, as they are stiff, large,

and heavy. Moreover, they are unique and of a

complexity that does not allow widespread use in

skiing as a consumer product.

Hermann, A., Carqueville, P., Baldinger, M. and Senner, V.

Measuring Pressure in Different Layers of the Ski Boot to Estimate Skiing Movements.

DOI: 10.5220/0010650700003059

In Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2021), pages 28-35

ISBN: 978-989-758-539-5; ISSN: 2184-3201

One option to reduce weight and size is to reduce

the degrees of freedom measured by the system.

However, force sensor systems measuring only the

vertical force are still heavy and, due to the

measurement principle, need to be very stiff. For

example the system by Wimmer and Holzner (1997)

had a total weight of 990 g.

An alternative to force measurement is the

measurement of pressure. With a known

measurement surface and pressure distribution, the

acting forces and moments can theoretically be

calculated. Pressure sensors are cheaper and can be

very thin and therefore minimize a possible restriction

of the athlete by the system itself. A flexible design

of pressure sensors is possible and allows the

integration inside a ski boot. Various systems of

different sensor types (resistive, capacitive, hydro

cells) have been used in research and are also

available as commercial products.

Drawbacks of pressure sensors are the limitation

on unidirectional measurements and the reduced

measurement frequency compared to force sensors

(depending on the measuring principle and the

number of sensors used, but usually lower than 250

Hz). Moreover, further limitations are a difficult

calibration when inside the boot (for example due to

shoe buckles and changing position of the foot inside

the boot), and the difficult determination of the force

application points (only possible for forces inside the

sensing area). As with all sensor systems, a

compromise between spatial resolution, time

resolution, measurement accuracy, robustness and

usability must be found for the intended use.

Nevertheless, pressure insoles were successfully

used in skiing research for various reasons. Krueger

et al. (2006) determined the edging angle and the

ground reaction force with a 24 sensor insole.

Raschner et al. (2001) used insoles with 99 capacitive

sensors to compare carving turns to (at that time)

traditional turns. Spitzenpfeil et al. (2006) tracked

mechanical loads in alpine ski racing and derived

implications for safety and material considerations

and Lafontaine et al. (1998) conducted a study with

PEDAR pressure measuring soles (Novel, Munich,

Germany) with professional Ski instructors. The

maximum and average vertical forces, the maximum

pressure, the pressure distribution, and the trajectory

of the pressure point was calculated for different

turns. In their congress abstract, Brodie et al. (2008)

propose, that pressure insoles can provide insight into

possible stance alteration to reduce knee torques or

aid preventive programs. An interesting work was

presented by Holleczek et al. (2010) who used self-

made pressure sensors (Holleczek et al. 2009) and

artificial intelligence to detect snowboard turns.

Falda-Buscaiot et al. (2017) studied the influence of

slope angle, foot position, and turn phase on the

plantar pressure distribution.

Stricker et al. (2010) compared forces calculated

with data from pressure measurement soles with

forces recorded by 3D dynamometers. The

compressive force measured by the soles were on

average between 21 % (outer ski) and 54 % (inner ski)

lower than that measured by the 3D dynamometers.

The authors attribute this to the different positions of

the measuring systems, as well as to the fact that part

of the force is absorbed in the boot shaft. However, a

high degree of similarity between the force-time

curves of the pressure measuring pads and the

dynamometers was found.

A sophisticated pressure sensing system was

presented by Schaff et al. (1997), who used a

measurement sock with 64 sensors attached beneath

the foot, as well as around the lower leg, the instep

and medially and laterally at the foot.

The use of pressure sensors, not only in the plantar

region of the foot, but also in the shaft, can add

valuable information and enable the estimation of all

force and moment components acting on the foot. A

system working on pressure sensors is preferable to a

system based on force sensors because it would be

easier to integrate in the existing equipment and

would be a lot cheaper. Especially an integration into

the outer shell of the ski boot would be relatively easy

Table 1: Advantages and disadvantages of resistive and capacitive pressure sensors.

Resistive Capacitive

+ simple sensor design + not sensitive to temperature and humidity

+ simple data logger design - complex data logger design

+ large measurement range - sensor thickness

+ fast reaction time

- non-linear

- sensitive to temperature and humidity

o records maximal pressure acting on the sensor

o records mean pressure acting on the sensor

Measuring Pressure in Different Layers of the Ski Boot to Estimate Skiing Movements

to manufacture and may have advantages to an

integration in the soft boot or sock with respect to

manufacturing and sensor robustness. On the other

hand, the pressure amplitude certainly is diluted

through the different material layers from the foot to

the outer shell.

For the development of sensors for measuring the

pressure distribution in a ski boot either capacitive or

resistive sensors are applicable.

The two technologies each have advantages and

disadvantages (

Table 1

) and the decision for a

technology depends on the application and the

resulting requirements. The most important

requirements for pressure sensors as well as their

practical application are summarized by Razak et al.

(2012) and mainly concern hysteresis, linearity,

temperature sensitivity, and the pressure range of the

sensor. In addition, the two pressure measurement

methods differ fundamentally with respect to the

measurement results. While resistive sensors measure

the peak pressure of the entire sensor surface, the

result of the capacitive measurement is the average

pressure over the sensor surface (Ashruf 2002).

Main aim of this study was to find the (1) number

of sensors and the (2) location of those sensors on the

foot needed to optimally estimate load states, and to

determine the (3) pressure differences between a

placement of sensors in the three layers between foot

/ sock, sock / liner, and liner / shell.

2 METHODS

For this study self-made prototype systems were

developed to measure pressure distribution in the ski

boot. In total three systems for the right foot were

built:

• PTBoot: Pressure sensors attached to the plastic

shell of the boot, between the shell and the inner

soft boot.

• PTSock: Pressure sensors attached to the inside of

the soft boot, between the soft boot and the ski

sock.

• PTFoot: Pressure sensors directly attached to the

foot.

This allowed to investigate the best location for the

sensors around the leg and test the loss of pressure

amplitude from one (material) layer to the next.

In a laboratory study, simulated skiing movements

were recorded simultaneously with all three systems.

Based on the results, a recommendation of a reduced

number of sensors is given. Fewer sensors allow

higher measurement frequencies and reduce

complexity of a to-be commercial measurement boot

and the required microcontrollers.

For the easy structure of the sensor and the

logging module, a resistive solution was chosen. The

two types of self-made sensors have a circular design

with a sensitive area of 30 mm in diameter and a

surface of 707 mm² (

Figure 1

) for a larger sensor and

20 mm in diameter and a surface of 314 mm² for the

smaller sensor. The sensors consist of a flexible

carrier foil of 25 μm thickness with 18 μm thick

copper tracks printed on it. The tracks form two

interlocking combs. The two conductive tracks are

wired for the connection to the data logger and a

reference conductor. Velostat

(electrically

conductive foil due to a carbon black impregnation,

3M, Maplewood, United States) was used as pressure

sensitive conductive material. Three layers, each 0.1

mm thick, were placed on the conductive side of the

foil. All layers were fixed and isolated by laminating

them with conventional laminating film. A voltage

divider circuit with a 100 Ω reference conductor was

used to record the sensor signal (see equation (2)).

Figure 1: Schema of the pressure sensor (left) and steps of manufacturing: middle left: foils with conductive tracks; middle

right: wired sensor foils; right: finished sensor with pressure sensitive conductive material layer over the foils with the

conductive tracks and protective, non-conductive foils laminated on both sides of the sensor.

icSPORTS 2021 - 9th International Conference on Sport Sciences Research and Technology Support

Figure 2: Sensor characteristic of the large sensor type

derived of 5 of the self-made pressure sensors.

𝑦𝑎𝑒



(1)

The sensor characteristics were determined

(Figure 2) by applying defined loads on the sensors.

An approximation curve was calculated using

equation (1) with the curve fitting tool of Matlab

2020a (MathWorks, Natick, Massachusetts,

USA).with 𝑦 being the pressure seen by the sensor, 𝑥

being the electrical resistance of the sensor, and the

parameters 𝑎  5.065 ∗ 10



, and 𝑏  0,1475 for the

large sensor type, having a corelation of 𝑅





0.9527 between pressure und electrical resistance.

Due to the small number of the smaller sensors the

sensor characteristics for each of the small sensors

was determined individually and is given in

Table 2

Table 2: Parameters for the sensor characteristic

approximation for the four small sensors used. Parameters

refer to equation (1).

Sensor a b R²

PTSock 6 125.1 0.01671 0.9286

PTSock 10 115.8 0.008495 0.9588

PTFoot 6 95.98 0.001639 0.9743

PTFoot10 370.5 0.0364 0.9775

The placement of the sensors was determined

based on preliminary tests and considerations with

regard to an optimal detection of following loads

acting on the foot, which are for-/backward leaning

(My) / rotation torque (Mz) /edging loads (Mx / Fy) /

vertical ground reaction force (Fz).

For all three prototypes 17 sensors were

distributed around the foot and lower leg (see Figure

3). Four sensors are placed on, both, the medial and

lateral side of the foot, five sensors were placed in the

plantar region, two sensors at the tibia shaft, one

sensor at the heel and one sensor above the instep. For

PTSock and PTFoot the sensors in the toe region no.

6 and 10, have a smaller diameter of 20 mm, due to

space limitations.

Figure 3: First line: Placement of the 17 pressure sensors o

ski boot prototype ‘PTBoot’ (placed on the inner side of the

hard shell of the boot). All sensors have a diameter of 30

mm. Second line: Placement of 17 pressure sensors in the

sock prototype ‘PTSock’ and the placement of the sensors

directly on the skin of the foot ‘PTFoot’. Sensors 6, and 10

are of a smaller diameter (20 mm). All other sensors have

diameter of 30 mm.

A myRio-1900 (National Instruments, Austin,

Texas, USA) was used for A/D conversion,

processing, and logging. To allow the logging of all

sensors, multiplexers (MUX, CD74HC4051E, Texas

Instruments, Dallas, Texas, USA) were used with

reference conductors ( 𝑅



 100Ω ). The

sensors were supplied with 𝑈



5𝑉. The resistance

of each sensor 𝑅



is calculated using equation

(2), were 𝑈



is the measured signal in Volt.

𝑅





𝑈



∗𝑅



𝑈



𝑈



(2)

A LabView 2015 (National Instruments, Austin,

Texas, USA) program was running on the myRio.

Measurement frequency was set to 10 Hz (limited by

the number of sensors and the hardware, e.g.,

switching time of the MUX). Data was saved on an

USB-stick plugged into the myRio-modul.

All three pressure sensing prototypes (Figure 4)

were used simultaneously. The setting of the data

collection is stationary. One participant is simulating

ski-typical body postures by shifting body weight and

using muscle activation.

Simulated postures are backward-leaning,

forward-leaning, left curve (inner edge of the

measurement boot), right curve (outer edge of the

measurement boot), internal rotation, and external

rotation. Each position was held for 5 seconds.

The pressure values were calculated using equations

(1) and (2) with the respective equation parameters of

the above-mentioned sensor characteristics. All

calculations were performed using Matlab.

Measuring Pressure in Different Layers of the Ski Boot to Estimate Skiing Movements

Figure 4: The three sensor prototypes and the test set up with the participant wearing all prototypes.

3 RESULTS

The comparison of the respective values of each

sensor of the different prototypes at the same position

indicate a qualitative similarity between the pressure

curves with a loss of amplitude from PTFoot to

PTSock to PTBoot (Figure ). The loss is not the same

for each sensor position. The pressure recorded by

PTBoot is low with values smaller than 0.125 N/cm²

for most of the sensors and not exceeding 10 N/cm²

in any sensor. The pressure range for PTFoot and

PTSock is mainly between 0 and 40 N/cm². Higher

values are reached by PTFoot sensor 2 (positioned

under the outside edge of the ball of the foot), which

reaches 68 N/cm² and PTFoot sensor 6 (positioned at

the medial side of the ball of the foot), which reaches

a maximum of 83.4 N/cm².

Both sensors under the ball of the foot (sensor 2

and 3) show highest pressure values in the plantar

region and have a distinguishable resolution of the

measured manoeuvres in all three systems. The

sensor positioned under the heel (sensor 5) hardly

measures any pressure for PTBoot but higher values

(about 10 N/cm²) for PTFoot and PTSock. The

sensors under the big toe (Sensor 1) of PTFoot and

PTSock show only small pressure responses to the six

skiing manoeuvres, with highest values for the time

spans of the transition from one manoeuvre to

another. The same sensor of PTBoot shows nearly no

signal. The different skiing manoeuvres are not

prominently expressed in the sensor data under the

arch of the foot (sensor 4), which recorded small

pressures over the total measurement. At the medial

and lateral side, the higher positioned sensors 8 and

12 of PTBoot show higher pressures than the lower

positioned sensors 6, 7 (medial) and 10, 11 (lateral)

of PTBoot. The same sensors of PTSock and PTFoot

give more pronounced values than the sensors of

PTBoot, but some signals of sensors 6, 7, and 12 show

an abnormal behaviour (see discussion). Even

though, the sensors at the calf (9 and 13) show high

pressures for PTFoot and PTSock, only low values

are recorded by PTBoot. At the tibia (sensors 14 and

15), the sensors of all three prototypes are sensitive to

the six skiing manoeuvres. Sensor 16 (backside of

heel) and 17 (instep) record high pressure and allow

to distinguish the skiing manoeuvres for PTFoot and

PTSock but record only low values for PTBoot.

4 DISCUSSION

In this study, PTBoot measured only very small

pressure values and the loss of amplitude from

PTFoot to PTBoot is large. Therefore, sensors for a

to-be measuring boot or sock need to be designed

very specifically with respect to resolution and

sensitivity and probably different sensor designs are

needed for different sensor positions in the boot. It

may be advisable to design the shell shape in such a

way that the liner transfers a large part of the force to

the shell on defined surface areas on which the

sensors are placed.

In general, the sock prototype produced the best

results compared to both other prototypes. This

prototype generates sensor values in the middle range

of the sensor characteristics for almost all sensors and

thus seems best suited for this application. Therefore,

an integration of such a pressure measurement system

in the sock or the liner would be more expedient than

the integration between the hard-shell and the liner.

On the other hand, with respect to robustness and easy

manufacturing, a pressure sensing boot is preferable

to a pressure sensing sock.

The qualitative determination of specific skiing

manoeuvres with a pressure measurement system in

the ski boot is possible. Based on the results of the

investigations with the three prototypes it is possible

to reduce the number of pressure sensors needed. A

recommendation of sensor positions based on

qualitative judgments is given in

Table 3

. The sensors

which show the most significant change in pressure

for the specific movements are highlighted in bold

letters.

To detect a forward or backward leaning body

position the tibia shaft may be better suited than a

icSPORTS 2021 - 9th International Conference on Sport Sciences Research and Technology Support

position at the calf or the plantar region. The sensors

at the calf are not only influenced by the leaning

position, but also by muscle activation. The sensors

in the plantar region may be non-optimal as they may

give misleading information in some situations. For

example, the sensors under the ball of the foot may be

unloaded even though the skier is leaning forward. In

such a case, the skier presses the tibia in the boot and

pulls the toes up to increase this pressure on the tibia

by increasing the pressure on the heel.

The exact selection of a sensor position at the

outer sides of the foot may heavily influence the

quality of results in detecting turns or rotation

movements. One issue to consider is the very

individual geometry of the foot, another reason is the

Figure 5: Comparison of the pressure sensor values of the three prototypes. The six skiing positions are indicated by the grey

areas and a respective annotation.

Table 3: Recommendation of the placement of pressure sensors to determine skiing manoeuvres based on the results with the

three prototypes.

Detection of Sensor Sensor position

Forward / backward lean (2), (3), 9, 13, 14, 15, 16,

(ball of foot), calf, tibia shaft, heel, instep

Left / right curve 8, 9 / 12, 13 Upper part of the lateral and medial side of the foot, near the bend of the

foot and the calf.

Internal / external rotation 6, 11 / 7, 10 Lower part of the lateral and medial side of the foot.

Measuring Pressure in Different Layers of the Ski Boot to Estimate Skiing Movements

clamping of the foot in the boot, which varies for

different skiing positions and manoeuvres but also as a

result of deliberate force production to control the ski.

If exact pressure values or loads should be

determined (in contrast to the estimation of body

position only), a great challenge will be the

calibration of the sensors. A commonly used

procedure for plantar pressure measurements is that

the persons foot is in the boot or shoe and the person

lifts the foot for a static and unloaded recording which

is then used to ‘zero’ the sensors. In the following

these values of the static recording are subtracted

from the later recorded values to determine the loads

acting on the foot. This procedure is not possible in

the prototypes used in this study. Even though the

lifting of the foot unloads the sensors placed under the

foot, the sensors positioned in other regions are

loaded. Moreover, a tight setting of the buckles of the

ski boot can produce high pressure values which even

may bring the sensors to a saturation.

The above given recommendation may only hold

for the detections of isolated and very specific

movements and will probably not be applicable if

multiple movement patterns occur simultaneously. A

possible solution approach to this could be the use of

artificial intelligence with a well-trained neuronal

network. As attractive as such a solution is, the

training of such a network would need sufficient real-

life data which also has to be labelled labour-

intensively.

Due to the design of the study, no high dynamics

are apparent, and the loads and pressures measured

with the prototypes are relatively low with most

sensors measuring values below 5 to 10 N/cm² and

only singular sensors reaching values of 20 to 40

N/mm². Up to ~ 6.4 N/cm

the pressure is

underestimated, due to the sensor characteristics

shown in Figure 2. Still, the values are small

compared to maximal (only plantar) pressure values

reported in on-slope skiing of 28 to 38 N/cm²

(Lafontaine et al. 1998).

As only the local maximal pressure of each

resistive sensor at each time is recorded, the system is

prone to large errors due to wrinkles in the sock, a

small hard object pressing on the sensor (for example

a stiff seam of the sock or inner boot or a bone of the

foot), or a bending of the sensor. This may also be a

reason for the, significantly, higher pressure signals

of single sensors of PTFoot compared to the other

prototypes (for example sensors 2, 3, 5, 6, 12).

Therefore, the use of capacitive sensors would be

advantageous, as local pressure peaks at the sensor

surface are filtered and a mean pressure of the sensor

surface is measured. But capacitive sensor designs are

more complicated and need specific experience.

The self-designed sensors used in this study are

non-linear and the approximation is not ideal. This

may lead to large errors in the calculation of pressure

values especially for very small and very high sensor

values. This is a result of various aspects of the sensor

design and, therefore, could be addressed in multiple

ways. For example, by replacing the Velostat

layers

by a carbon black silicon compound, potential contact

loss between the Velostat

layers themselves and

between Velostat

and the printed circuit board

material may be prevented. This contact loss results

in higher electrical resistance and thus lower pressure

values.

5 CONCLUSION

This work shows the relevance of certain sensor

positions for detecting the simulated load states. Two

groups of sensors should be emphasized here: the

anterior shaft sensors (Sensors 14 and 15) for

determining a forward/backward lean, and the sensors

on the lower part of the lateral and medial side of the

foot for determining an internal/external rotation.

In general, the sensor design must be specifically

made for the respective position and the

corresponding pressure value range. Here the sock

prototype shows the most balanced sensor values for

the different sensor positions. To tackle the various

challenges with respect to an optimal sensor design

(for example, measurement range, saturation, and

sensor size), field data will be needed to allow more

insights.

Injuries of the knee in alpine skiing often result

from a backward leaning position (Freudiger and

Friedrich 2000). Therefore, the implementation of a

measurement boot recording external loads and body

positions in an adaptive safety system (for example a

future mechatronic ski binding) may allow to detect

risky situations and react accordingly. A combination

of force sensors measuring torques around the vertical

axis and pressure sensors used to predict forward and

backward lean and torques in the sagittal plane might

be a possible compromise.

Artificial Intelligence may allow to cope with the

high complexity due to imperfect defined sensor

characteristics. A neuronal network with a small

number of pressure sensors at defined positions could

be trained with ground reaction forces (My, Mz, Fy,

Fz) recorded by a measurement binding. With

sufficient training data, the neuronal network will

predict the skiing loads using the pressure sensor data.

This has been successfully done for a snowboard

binding by Holleczek et al. (2010).

icSPORTS 2021 - 9th International Conference on Sport Sciences Research and Technology Support

REFERENCES

Ashruf, C.M.A. (2002): Thin flexible pressure sensors. In SR

22 (4), pp. 322–327. DOI: 10.1108/02602280210444636.

Brodie, Matthew; Walmsley, Alan; Page, Wyatt (2008):

Fusion motion capture: a prototype system using

inertial measurement units and GPS for the

biomechanical analysis of ski racing. In Sports Technol.

1 (1), pp. 17–28. DOI: 10.1002/jst.6.

Falda-Buscaiot, Thomas; Hintzy, Frédérique; Rougier,

Patrice; Lacouture, Patrick; Coulmy, Nicolas (2017):

Influence of slope steepness, foot position and turn

phase on plantar pressure distribution during giant

slalom alpine ski racing. In PloS one 12 (5), e0176975.

DOI: 10.1371/journal.pone.0176975.

Freudiger, S.; Friedrich, N. F. (2000): Critical load cases for

knee ligaments at skiing - an engineering approach. In

ASTM Special Technical Publication (1397), pp. 160–174.

Holleczek, Thomas; Ru, Alex; Harms, Holger; Tro,

Gerhard (2010): Textile pressure sensors for sports

applications. In : 2010 IEEE sensors. Waikoloa,

Hawaii, USA, 1 - 4 November 2010 ; [the Ninth IEEE

Sensors Conference 2010. 2010 Ninth IEEE Sensors

Conference (SENSORS 2010). Kona, HI, 11/1/2010 -

11/4/2010. Institute of Electrical and Electronics

Engineers; Sensors Council; IEEE Sensors Conference.

Piscataway, NJ: IEEE, pp. 732–737.

Holleczek, Thomas; Zysset, Christoph; Arnrich, Bert;

Roggen, Daniel; Troster, Gerhard (2009): Towards an

Interactive Snowboarding Assistance System. In :

Proceedings / 2009 International Symposium on

Wearable Computers. ISWC 2009 ; 4 - 7 September

2009, Linz, Austria. 2009 International Symposium on

Wearable Computers (ISWC). Linz, Austria, 9/4/2009

- 9/7/2009. International Symposium on Wearable

Computers; Institute of Electrical and Electronics

Engineers. Los Alamitos, Calif.: IEEE Computer

Society, pp. 147–148.

Kiefmann, Andreas; Krinninger, Maximilian; Lindemann,

Udo; Senner, Veit; Spitzenpfeil, Peter (2006): A New

Six Component Dynamometer for Measuring Ground

Reaction Forces in Alpine Skiing. In : The Engineering

of Sports 6, vol. 21. New York, NY: Springer, pp. 87–

92, checked on 11/17/2019.

Krueger, A.; Edelmann-Nusser, J.; Spitzenpfeil, P.; Huber,

A.; Waibel, K.-H.; Witte, K. (2006): A measuring

method for combined determination of the edging angle

and the ground reaction force in alpine skiing. In E.

Müller (Ed.): 24 International Symposium on

Biomechanics in Sports. With assistance of H.

Schwameder, G. Strutzenberger, V. Fastenbauer, S.

Lindinger. 24 International Symposium on

Biomechanics in Sports. Salzburg, July 14-16, 2006.

Lafontaine, D.; Lamontagne, M.; Dupuis, D.; Diallo, B.

(1998): Analysis of the distribution of pressures under the

feet of elite alpine ski instructors. In H. J. Riehle, M. M.

Vieten (Eds.): 16 International Symposium on

Biomechanics in Sports. 16 International Symposium on

Biomechanics in Sports. Konstanz, July 21-25, 1998.

Razak, Abdul Hadi Abdul; Zayegh, Aladin; Begg, Rezaul

K.; Wahab, Yufridin (2012): Foot plantar pressure

measurement system: a review. In Sensors, pp. 9884–

9912. DOI: 10.3390/s120709884.

Saito, Ayuko; Doki, Hitoshi; Kondo, Akiko; Hirose,

Kiyoshi (2015): An Attempt for Developing the

Measurement System of Reaction Force from Snow

Surface for Private Ski Boots by Compact Force

Sensors. In Procedia Engineering 112, pp. 326–331.

DOI: 10.1016/j.proeng.2015.07.257.

Schaff, P.; Senner, V.; Kaiser, F. (1997): Pressure

distribution measurements for the alpine skier - from

the biomechanical high tech measurement to its

application as Swingbeep-feedback system. In Erich

Müller (Ed.): Science and skiing. 1st ed. London, New

York: E & FN Spon, pp. 159–172.

Schwameder, H.; Nigg, B.; Tscharner, V.; Stefanyshyn, D.

(2001): The effect of binding position on kinetic

variables in alpine skiing. In Erich Müller (Ed.):

Science and skiing II. Tagungsband ; St. Christoph a.

Arlberg, Austria, January 9 - 15, 2000. With assistance

of H. Schwameder, C. Raschner, S. Lindinger, E.

Kornexl. Hamburg: Kovač (Schriftenreihe Schriften

zur Sportwissenschaft, 26), pp. 43–54.

Spitzenpfeil, P.; Huber, A.; Waibel, K. (2006): Mechanical

load and muscular expenditure in alpine ski racing. In

E. Müller (Ed.): 24 International Symposium on

Biomechanics in Sports. With assistance of H.

Schwameder, G. Strutzenberger, V. Fastenbauer, S.

Lindinger. 24 International Symposium on

Biomechanics in Sports. Salzburg, July 14-16, 2006.

Stricker, Gerhard; Scheiber, Peter; Lindenhofer, Elke;

Müller, Erich (2010): Determination of forces in alpine

skiing and snowboarding: Validation of a mobile data

acquisition system. In European Journal of Sport

Science 10 (1), pp. 31–41. DOI:

10.1080/17461390903108141.

Wimmer, M. A.; Holzner, R. (1997): Constraint Forces may

influence the measurement of vertical ground reaction

forces during slalom skiing. In Erich Müller (Ed.):

Science and skiing. 1st ed. London, New York: E & FN

Spon, pp. 208–215.

Measuring Pressure in Different Layers of the Ski Boot to Estimate Skiing Movements