Development and Implementation of Mobile Apps for Skier

Training System

Kim

Yong Wook and Kim Ju Yong

Department of Sports & Well-Being, HanYang University, Ansan, 15588, Korea

Keywords: Skier Training System, Mobile Apps.

Abstract: Most skiers who use smartphones carry them when they ski. Lately internet connection is getting better and

there can be active information exchanges between applications installed in smartphones and online operating

servers. In addition, with the use of GPS, smart phones can precisely track skier's locations and record the

real time information of the gyroscope sensors connected to the Bluetooth of smart devices. This study aims

to design and develop a mobile application which can monitor ski trails and analyze ski postures with the help

of smartphones technology. For this reason, our mobile application was developed based on Android SDK

4.2 version using Java, and C-language. To measure the information of the skier's posture, a belt with several

gyroscope sensors was developed. It records the postures of the skiers who wear the belt when they move

their body from side to side and back and forth. Through the application's calculations of the skier's speed and

directional turning track data, skiers can know what modifications they need to make in order to improve their

techniques and adjust their postures. This mobile application can exchange information with online operating

servers with the use of 3G and Wi-Fi. In addition, it operates as a background program in smartphones and

starts recording and analyzing when skiers start skiing at designated ski resorts.

1 INTRODUCTION

Since the development of computers and their

practical uses in a daily life, many studies have been

found particularly in the sports training sector. The

computer has been used helpfully in finding the most

effective method to accurately measure and improve

the exercise ability of an elite athlete. As computers

develop, various scientific sports programs are being

developed to measure and record the physical ability

of athletes and manage their conditions. Recently, the

current existing research environments have been

expanded along with the emergence of smartphones.

In the past, a number of sensors were attached to an

athlete’s body, and then the sensors needed to be

connected to a computer by wire in order to measure,

in detail, the exercise records of elite athletes. Such

devices, however, posed some issues, such as

uncomfortable or unnatural movement of athletes,

and network disconnection while recording.

Now smartphones can replace the computer.

Smartphones use a ‘Mobile Communication Network’

and are connected to other computers anytime and

everywhere if connected to internet network. In

addition, GPS, gyroscope sensors, acceleration

sensors, illuminance sensors, and other sensors

embedded in smartphones can collect various types of

information (Dobkin and Bruce, 2013). Therefore,

smartphone-based information collecting can be free

from the location limits. Also wired smartphone

connections can be resolved through various sensors

in the Bluetooth wireless module. Along with the

development of various equipment including

smartphones, many developments and studies are on-

going to improve the athletic skills of elite athletes

(Chardonnens and Julien, 2014). The studies

requiring massive human resources and investments

as to improve the athletic skills of an elite athlete are,

of course, important. However, additional studies on

‘Sports Training Apps’ are also needed to boost

simple and convenient uses in ordinary people. The

studies on mobile apps helpful to improve users’

lifestyles are also performed in medical sector as well.

Various apps are developed for the purpose of

treating or adjusting the patients, such as mobile apps

for correcting patient’s incorrect posture or for

inducing an active lifestyle in teenagers (Gefen et al.,

2015; Lubans and David, 2014; Hidalgo-Mazzei et al.,

2015). If users use the above mobile apps well, it

definitely helps to achieve users’ treatment or

adjustment purposes (Recio-Rodríguez et al., 2014;

214

Wook, K. and Yong, K..

Development and Implementation of Mobile Apps for Skier Training System.

In Proceedings of the 3rd International Congress on Sport Sciences Research and Technology Suppor t (icSPORTS 2015), pages 214-221

ISBN: 978-989-758-159-5

Al-Hadithy et al., 2012). Smartphones are considered

a convenient device for users since users can install

and use various mobile apps in their smartphones. In

other words, users can use various mobile apps by

simply downloading apps from the app store and

installing it into their smartphones (Chittaro et al.,

2014).

If users have a strong will for training, ‘Sports

Training APPS’ can achieve their desired training

performance without temporal or location limitations.

Through these apps, users can control their own skill

and check their exercise logs to get a self-feedback.

Usually athletes had to check their training logs

monitored by a third person, but app users can

achieve their skill improvements themselves through

a self-report (self-feedback) (Saw et al., 2015). If

skiers have access to a monitoring tool that enables

them to check their downhill record, it would be

helpful to improve their skiing skills. Therefore, the

purpose of this study is to design mobile apps that are

required for skiers and to explore the applicability and

effectiveness of mobile apps at the ski slope. This

study is to help in designing convenient mobile apps

for skiers who use smartphones. The mobile apps

designed in this study include a monitoring feature for

skier’s exercise logs and postures.

2 RESEARCH APPROACH

The mobile apps in the “Health and Fitness” sector

that are currently available in the app store are in a

ranking order from ‘Providing instruction on how to

perform behavior’, ‘Modeling/ demonstrating

behavior’ to ‘Providing feedback on performance’ (C

onroy et al., 2014). The sector is further classified into

3 broad parts: ‘Health Training Apps’, ‘Exercise

Tracking Apps’ and ‘Motion Tracking Apps’. First,

the key functions of ‘Health Training Apps’ include

the followings. The users themselves exercise with

their own posture as guided by a personal trainer in

the video (7 Minute Workout, 2015; Daily Workout,

2015; Sworkit, 2015). First, the trainees learn about

exercising for their health training. Next, the trainees

determine the exercise type based upon their purpose

of exercise (weight loss, muscular strength, etc.).

Based on the exercise type determined by the trainees,

the exercise program, recommended by their ‘Health

Training Apps’, are then executed. Their exercise

logs are then saved in their smartphones so the users

can investigate their exercise logs at a glance.

However, such exercise programs pose the following

problems. Users exercise without measuring the

individual exercise intensity. Health trainers at fitness

clubs draw an exercise program considering various

variables of their trainees. All items from the

measurement of basic exercise unit, ‘1RM’, intensity

from exercising to muscular training should be

accurately determined. However, ‘Health Training

Apps’ require all users to enter all variables, posing

the possibilities that the incorrect variables may be

entered. This further poses limits of creating an

accurate exercise program suitable to each individual.

This problem associated with the variables that

should be directly entered by users are also found in

mobile apps in other sectors. ‘Health Training Apps’,

which should suggest an exercise prescription

without accurately checking the personal

characteristics of users, pose a limitation to a ‘General

Exercise Prescription’. Despite these limitations, this

program continues to grow and develop to improve

user’s convenience (Parikh et al., 2014). Therefore,

various variables should be considered in developing

‘Health Training Apps’ as well as to avoid from

making an incorrect exercise program.

Second, ‘Exercise Tracking Apps’ are considered

to be nearly complete. Apps are either already

embedded in the smartphones since their release or

additionally sold from App Stores. The similarity of

these apps are that the user’s movements are

measured by a GPS-based location traceability or

gyroscope sensors embedded in smartphones or

smartwatch (endomondo, 2015). If users perform an

outdoor exercise such as running or biking, these apps

enable tracking and recording of the user’s route and

speed very accurately. In addition, the outdoor

environment such as local weather information is

provided to give the users various logs. Also, users

can make up their own exercise routes using the

information shared by other users. People who

actively use these ‘Exercise Tracking Apps’ can

easily post and share their individual exercise logs

and lifestyles on social media.

Third, ‘Motion Tracking Apps’ adjust users’

position when they exercise using some equipment.

These ‘Motion Tracking Apps’ are already vitalized

in the golf sector and are available on the market now

(Nike Golf 360° App, 2015). A device attached on a

golfer’s hat that serves as a guide for the distance

from the hitting point to hole on the golf field is

successfully commercialized these days (Voice

Caddie, 2015). In addition, there are other apps that

analyze the user’s swing posture to instruct the

correct posture while swinging via a device attached

on the golf club (3baysGSA, 2015). Other apps are

being developed and sold in the tennis sector. It

requires a device attached on a tennis racket to

analyze the user’s tennis swing and proposes an

Development and Implementation of Mobile Apps for Skier Training System

215

accurate hitting point (Smart Tennis Sensor, 2015).

These products are operated by attaching a simple

device on the sporting goods that are connected to

smartphones by Bluetooth to trace and record

exercise motions. The major manufacturers of

sporting goods, such as ‘Nike’ and ‘SONY’, are

selling the mobile apps in popular sports such as golf

and tennis for sports maniacs. Once the maniacs are

satisfied with the mobile apps, the customer

satisfaction in the existing business area is also

improved (Budd and Vorley, 2013). The reason why

many major global manufacturers of sporting goods

are selling mobile apps and various accessories is to

maintain consumer’s loyalty on their brand.

Therefore, the market in sports mobile apps is

expected to continuously grow.

Downhill skiing as a sport requires a basic

downhill technique. Most ordinary skiers enjoy going

downhill at ski resorts. Downhill skiing requires

skiers’ technique to safely ski down the slope. In

order to go down the hill safely, the skier should focus

his or her body weight at an accurate center point. The

body angle should be properly tilted toward the inner

turning axis in order for skiers to stably spin at a fast

speed. The body angle should be changed in

proportion to speed and turning radius. The skiers

learn the proper body angles through their experience

with skiing. If skiers could be advised on how to

control their body angle, it would be very helpful for

them to acquire an advanced skill. In this study, the

location of a skier collected via GPS is analyzed to

check the skier’s downhill records. Therefore this

study is to assist in the design of ‘Skier Training Apps’

that propose a proper body angle at a specific location.

The location of a skier is collected via GPS and the

skier’s posture is recorded in the smartphone via

gyroscope sensors. The information recorded in the

smartphone is saved on an operation server in a real-

time manner. In addition, the proper body angle at a

particular location is calculated and recorded by an

operation server at the same time. Skiers can check

their performance logs after skiing. The operation

servers then advise the skiers their best body angle at

each turning posture.

3 PROPOSED METHODOLOGY

FOR DESIGN AND DEVELOP

MOBILE APPS

The purpose of this study is to develop a ‘Skier

Training System’ that collects and analyzes the

skier’s posture information in a real time manner.

These days, the hardware embedded in our

smartphones have been highly developed into the

same level as personal computers. However,

smartphones require and use many resources in order

to perform the basic functions of phone, such as

calling, messaging, etc. Thus, smartphones pose

difficulty in multi-tasking. ‘Skier Training Apps’

designed in this study, collect information and

transfer them onto an operating server as a primary

role. Instead of required calculations being done on

our phones, they are rather calculated on an online

operating server. In other words, the required

calculations such as ‘R.A.A. (Recommend Angle

Adjustment)’ are performed on an operating server.

3.1 Skier Training System Diagram

This study is broadly designed with two subparts: 1)

‘Skier Training Apps’ operated on smartphones; and

2) ‘Operating servers’. The information collected by

smartphones is uploaded onto the operating server in

a real-time manner (Figure 1).

If the information fails to upload due to poor

network connections, it is temporarily saved in the

smartphone and then automatically uploaded later

once the network is back online. In the operating

server, the database system is operated to manage the

user’s information. The identification number and

user ID are both used as the user’s identification

information. When operating the ‘Skier Training

Apps’ in the smartphone, the app continues to operate

in a ‘background process’ and automatically collects

information. This ‘Skier Training App’ automatically

performs its function as soon as the skier arrives at the

ski resort. The ski resort maps that are shared among

the apps, are constantly updated with new

information.

3.2 Development Environment

The operating server system is composed of a

database system and communication system. The

database system is built based on ‘Oracle Database

12c’. The communication system with ‘Skier

Training Apps’ is made using an ‘XML’. The ‘Skier

Training Apps’ are developed using the Android SDK

4.2 version, Java, and C-language. In the smartphones,

the low priority process may be exited without prior

warning in order to ensure the necessary resources to

execute an application program. For this reason, the

users of ‘Skier Training Apps’ have voiced-guided

logs for skiers once they take a lift for skiing. The

users can listen to real time log broadcasts and know

the operation status of their ‘Skier Training Apps’.

icSPORTS 2015 - International Congress on Sport Sciences Research and Technology Support

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Figure 1: Skier Training System Diagram.

3.3 Information Gathering

‘Skier Training Apps’ that are being used in the skiers’

smartphones are connected to two different sensors

which are responsible for collecting downhill ski

records from a skier. One of the sensors, GPS,

collects the data of the skier’s current location. If at

least three or more GPS signals are received, an

accurate location within five meters of the skier can

be collected. The collected GPS information is

combined with the location data from the user’s

‘Mobile Phone Network’ to give a more accurate

location of the skier. The other sensor is a gyroscope

sensor that checks the posture of the skiers. Once the

skier puts on the gyroscope sensor belt and connects

it with his or her smartphone via Bluetooth, the

gyroscopes on the belt will be activated and ready to

Figure 2: Gyroscope Sensors Belt.

use (Figure 2). Once a skier skis downhill, the

position is recorded in a real-time manner via the

gyroscope sensors in the smartphone and then

uploaded to the operating server.

3.4 Mobile Apps Design

‘Skier Training Apps’ are designed to be

automatically executed without requiring a special

operation. ‘Skier Training Apps’ are also designed

intuitively. The skier completes all preparations by

pushing the start button. A skier only needs to check

the operation of the ‘Skier Training App’ once prior

to skiing. Once the ‘Skier Training App’ is activated,

the skier will be accurately voice-guided based on his

or her travel distance and speed.

If the ‘Skier Training App’ is already executed

while the skier is going to the ski resort, it works in

the background of the smartphone’s operation to see

whether the skier gets on a ski-lift or not. Once it has

been confirmed that the skier takes a ski-lift, the

skier’s activity information will be automatically

saved on the operating server (Figure 3). Even though

the skier forgets to turn off the app once he or she

leaves the ski resort, the app will automatically turn

off for the skier’s sake. This function automatically

operates without pressing the ‘stop’ button after

skiing. As soon as a skier leaves the ski resort, the app

stops recording by itself. Skiers can check their ski

logs while resting (Figure 4). The log is recorded and

listed by ‘Season’, ‘Location’, and ‘Date’. Each log

enables users to check their exercise routes, positions,

etc.

Development and Implementation of Mobile Apps for Skier Training System

217

Figure 3: Exercise Recording.

Figure 4: Skier Training Record.

4 FINDINGS AND ANALYSIS

The field tests of the ‘Skier Training App’ was

performed at five different ski resorts in Korea and

three ski resorts in Japan during the 2014 and 2015

season. Five different smartphone types including the

Samsung Galaxy S5 were used in this experiment. A

total of six skiers participated in the test. The level of

GPS signals that were received were different in

every resort. Although the signal strengths (three or

more) that were received from the GPS satellites were

different at every resort, there was no problem with

the accuracy of the skier’s location. The

disconnection points due to weak GPS signals while

skiing were also observed.

At times when the skier skis in an area that is not

found by the GPS satellites, the operating server will

predict and come up with the missing location info by

calculating the last known position with the current

one. Additionally, the location information via GPS

data and ‘Mobile Phone Network’ will be adjusted

and updated on the operating server (Figure 5).

Figure 5: Track Route.

The standard time used in calculations were not based

on GPS time but the operating server’s time

regardless of different time zones. The time that is

shown in the ski log in the same as the user’s

smartphone time. The speed of a skier was calculated

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by 3-D coordinates through the skier’s latitude,

longitude, and altitude (Figure 6). The irregularity of

travel route was not considered.

Figure 6: Three-Dimensional Calculation Formula.

However, more than a ten meter deviation was

found in the attitude information received by the GPS;

so a ‘Google Elevation API’ was used to adjust the

GPS altitude. A skier’s speed was calculated

considering a 10-second long skier’s distance as the

basic unit. The skier’s speed was recorded every 0.5

seconds and the recorded speed 60 different

linearized measurements. Incorrect speed records on

the linear graph were adjusted and removed.

Posture information collected via the gyroscope

sensors were measured and calculated more precisely

than speed. Once changes in the skier’s posture were

detected by the gyroscope sensors, the sensor

information collected at every 0.1 second. The

information collected 50 linearized postures so the

skier’s posture change data was more accurately

calculated and recorded (Figure 7).

Figure 7: Linear Graph of Speed.

Skiers rarely check their smartphones while going

downhill so real-time R.A.A. (Recommended Angle

Adjustments) were not calculated. The R.A.A. is

calculated as soon as the skier uploads his or her

location and posture data onto the operating server.

The users can receive their feedback when they check

their records while resting after skiing (Figure 8). The

R.A.A. was calculated based on the body angle

proposed in the ‘Downhill Posture Research of

Alpine Skiers’ (Lee et al., 2013; Scheiber et al., 2012).

Other than the recommended body angle of the

‘Downhill Posture Research of Alpine Skiers’, our

test skier’s body angle was also calculated

considering the skier's speed and directional turning

track data.

5 CONCLUSION

Even though skiers are eager to develop their ski

skills, not many of them improve their skills in the

master level training course. By using ‘Skier Training

Apps’ developed in this study, among other things,

skiers will be able to check their downhill trajectory.

The skiers are also able to check their downhill

position at a particular location. The body angle of a

skier changes based upon the skier’s speed and

turning radius when turning while skiing downhill.

Then the information collected is analyzed to

recommend a skier the best body angle for

improvement. Therefore, the skier makes an effort to

improve his or her downhill skiing position compared

to the recommended body angle. This is a mobile app

that enables skiers to check and adjust their posture,

definitely helps skiers to improve their skiing

techniques. In addition, the skiers can check their ski

log data such as duration, distance, burnt calories, etc.

This information helps skiers to establish their own

exercise plan during the winter season. Therefore,

‘Skier Training Apps’ developed through this study

produced the following results.

Figure 8: Recommend Angle Adjustment.

First, skiers can check their own ski log. The

location collected via GPS is analyzed to record

skier’s travel route. Next, detailed information such

Development and Implementation of Mobile Apps for Skier Training System

219

as longitude, latitude, and altitude are calculated for a

skier’s particular location to give a recommended

‘Average Speed’, ‘Maximum Speed’, ‘Turning

Radius’, etc. The personal information previously

entered, such as skier’s weight, height, age, etc., can

estimate the calorie consumption. The above

information is gathered so the skiers can set up their

own exercise plan.

Second, skiers can adjust and improve their posture.

The most important things for downhill skiing

postures are ‘Joint Angles’ and ‘Body Angles’. The

‘Body Angle’ is measured in this study. The

information recorded from ‘Mogul Ski’ and ‘Slalom’

sports that require instant quick movements of pros,

is not consistent with this study. This study has

analyzed the ‘Middle Turn’ and ‘Long Turn’ done by

ordinary skiers while predicting their downhill

postures. The body angle is served as a very crucial

factor for downhill postures. ‘Skier Training Apps’

developed in this study analyzed the skier’s ski

information (speed, turning radius) to recommend the

proper body angle. However, the R.A.A proposed in

this study is resulted from a simple mechanical

calculation without considering the skier’s height,

weight, and age. The R.A.A. is provided as reference

information for the skier, which is not an essential

thing that the skier must follow.

Third, the ‘Exercise Management Program’ was

first used by elite athletes and then ordinary skiers.

All people who enjoy sports desire to improve their

sports technique. Elite athletes are systematically and

scientifically managed by a training system of a

professional coach for their athletic abilities and

performance. This kind of management and coaching

helps to improve their athletic abilities. Ordinary

skiers can also use ‘Exercise Management Program’

mobile apps to manage their skill.

Smartphone app technology information has been

developed from the user’s view, analyzed, and

applied. For example, mobile apps that enable dieters

to check their food consumption and calories via

voice instruction has already been developed (Sun et

al., 2015). In addition, smart mini-screens attached

inside of skier’s goggles to provide skier’s

information such as their skiing time, distance,

altitude, etc. is already available on the market (Zeal

Optics, 2015). Applying this technology proposes

additional studies shown in the following.

A combination of a camera that can be installed on

a skier’s goggles to analyze the downhill route and a

sensor attached to the skier’s legs to measure and

record joint angle information can produce data that

can give audio suggestions for the skier while skiing.

In addition, if there are foot pressure sensors that are

attached in the skier’s boots, the most precise and

stable posture can be proposed to the skier. It can be

integrated with wearable devices, such as chest sensor

belts, which are already available on the market, that

can measure heart rates (Banos et al., 2014). As

mentioned above, various types of physical

information of skier’s can be collected. Therefore, the

best exercise program can be recommended using

data collected for comprehensive calculation.

More studies are required on the development of

various sensors to collect skier’s exercise data, as well

as how to process the collected information. All

studies should be conducted by user interface from

user’s view for easy and simple uses and they also

should be designed based on the strategy applicable

to the sales market (Boudreaux et al., 2014). Most of

the current available mobile apps enable the users to

record their own exercise and give self-feedback to

themselves (Middelweerd et al., 2014). If the users

check their training contents and make an effort to

improve their skill, the mobile app definitely helps

them to improve it (Cranwell et al., 2014; Glynn and

Liam, 2013; Direito et al., 2015). If skiers properly

use the information proposed in this study, their

techniques and exercise skills are sure to improve.

ACKNOWLEDGEMENTS

We would like to thank the anonymous reviewers for

their helpful comments on an earlier version of this

paper.

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