Exercise and Wellness Health Strategy Framework

Software Prototype for Rapid Collection and Storage of Heterogeneous Health

Related Data

Petr Br˚uha

1, 2

, Roman Mouˇcek

1,2

, Pavel

Snejdar

, David Bohmann

, V´aclav Kraft

and Peter Rehor

Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia,

Univerzitn´ı 8, Pilsen, Czech Republic

NTIS - New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia,

Univerzitn´ı 8, Pilsen, Czech Republic

Keywords:

Exercise and Wellness, Chronic Disease, Health Related Data, Health Informatics Systems, Software

Prototype.

Abstract:

Unwillingness of many people to assume responsibilities for a personal health, ﬁtness and wellness seems to

be widespread. This can be partially remedied by individualized exercise and wellness program that integrates

the basic knowledge domains: lifestyle, sports and ﬁtness, and nutrition and personal/environmental health.

However, collection, management and analysis of data and metadata related to these domains is demanding

and time consuming task. Moreover, the appropriate annotation of raw data is crucial for their next process-

ing. To promote such a program a software infrastructure for collection, storage, management, analysis and

interpretation of health related data and metadata has been proposed and part of this infrastructure has been

developed and tested outside laboratory conditions. This software prototype allows experimenters to collect

various heterogeneous health related data in a highly organized and efﬁcient way. Data are then evaluated and

users can view relevant information related to their health and ﬁtness.

1 INTRODUCTION

In the countries of the European Union (EU) deaths

due to chronic diseases are projected to increase. It

was estimated that out of the projected millions of

people who would die by 2015, 64% of them die

of a chronic disease – unless urgent action is taken

(Tunstall-Pedoe, 2006). Given that both physical in-

activity and obesity are strong independent causes

and predictors of chronic illness and disability, it has

been estimated that they impose a signiﬁcant eco-

nomic burden on the health-care system in EU. The

most recent research in EU indicates that only 7.5%

of children and 15% of adults are physically active

for at least 150 minutes per week, while over 18%

are obese and over 46% are overweight (Busse, 2010;

Organization et al., 2010; Webber et al., 2014).

It is apparent that physical activity is essential in

the prevention of chronic disease and premature death

(Lee and Skerrett, 2001). Chronic diseases develop

over ones lifetime, with clinical symptoms occurring

many years after the underlying origins of the disease

have occurred. As we move ahead in the 21st century,

cardiovascular diseases, i.e. coronary artery disease

(CAD) hypertension, stroke, and heart failure, type

2 diabetes, metabolic syndrome, and cancer are the

leading killers in westernized society and are increas-

ing dramatically in developing nations. Physical inac-

tivity is a modiﬁablerisk factor for cardiovasculardis-

ease and a widening variety of other chronic diseases,

including diabetes mellitus, cancer (colon and breast),

obesity, hypertension, bone and joint diseases (osteo-

porosis and osteoarthritis), and depression 1-14 (Tay-

lor et al., 2004; Blair et al., 2001; Shephard, 2001).

The onset of progression of chronic diseases is

mediated in the vast majority of cases by an interac-

tion between genetic factors and their interaction with

environmental factors. These environmental factors

are largely lifestyle factors, namely physical activity

and dietary patterns, but also include other inﬂuences,

such as smoking, alcohol consumption, stress, and

hazardous environmental compounds. These factors

are modiﬁable, and, as such, disease manifestations

from these factors are largely preventable.

To cope with these modiﬁable factors exercise and

wellness intervention programs have been introduced,

mainly in the United, States, Canada and Australia.

This paper presents the ﬁrst steps that have been done

BrÅ

rha P., MouÄ ek R., Å

anejdar P., Bohmann D., Kraft V. and Rehor P.

Exercise and Wellness Health Strategy Framework - Software Prototype for Rapid Collection and Storage of Heterogeneous Health Related Data.

DOI: 10.5220/0006296604770483

In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), pages 477-483

ISBN: 978-989-758-213-4

477

to introduce such exercise and wellness health strat-

egy framework and related academic program within

the European Union. Its attempt is to create profes-

sionals who are capable inﬂuence self-care practices

positively, reinforce healthy habits and prepare re-

sponsible citizens for the future. This innovative, ap-

plied and unique initiative combines three tradition-

ally exclusive disciplines (Etiology of Chronic Dis-

ease, Exercise Science and Behavioral Psychology)

into one comprehensive curriculum that addresses

two major front page challenges in Europe: chronic

disease management and sedentary lifestyle. It is be-

ing applied through extensive clinical and ﬁeldwork

experiences, the degree will provide students with the

theoretical knowledge, practical skills, and prerequi-

sites that are necessary to provide a professional guid-

ance during lifestyle changes.

Such exercise and wellness health strategy frame-

work needs a supportive software infrastructure that

besides others promotes collection of health related

data and metadata followed by their further annota-

tion, processing and visualization. This paper intro-

duces the ﬁrst version of such software infrastruc-

ture,a software prototype that focuses on deﬁnition

and automation of the data collection process in order

to capture a huge amount of heterogeneous health re-

lated data from many users in various environment in

a short time. It is assumed that the procedure of data

collection has to be as short and user friendly as pos-

sible to signiﬁcantly promote the initial participants’

motivation to cope with the most important step, a de-

sired change of participants’ behavior leading to their

better physical, emotional and mental health.

The paper is organized in the following way.

The next section discusses some questions related to

chronic illnesses, personal physical, emotional and

mental well-being and the necessity of exercise and

wellness strategy framework to cope with these mat-

ters. The third section introduces a supportive soft-

ware infrastructure for such a framework. The sub-

sections then present the ﬁrst version of this software

infrastructure from architectural, implementation, de-

ployment and testing points of view. The last section

brings concludingremarks and introduces future steps

and improvements.

2 EXERCISE AND WELLNESS

HEALTH STRATEGY

FRAMEWORK

Chronic illness has profound effects on a persons

physical, emotional, and mental well-being, which of-

ten make it difﬁcult to carry on with daily routines and

relationships. Over the past decades, considerable

knowledge has accumulated concerning the signiﬁ-

cance of exercise in the treatment of a number of dis-

eases, including diseases that do not primarily mani-

fest as disorders of the locomotive apparatus. Today,

exercise is indicated in the treatment of a large num-

ber of additional medical disorders. In the medical

world, it is traditional to prescribe the evidence-based

treatment known to be the most effective and entail-

ing the fewest side effects or risks. The evidence sug-

gests that an exercise therapy is just as effective as

medical treatment in selected cases and even more ef-

fective or improving the ﬁnal effect in special situa-

tions. In this context, exercise therapy does not repre-

sent a paradigm change, it is rather that the accumu-

lated knowledge is now so extensive that it has to be

implemented.

There is a growing interest in the use of exercise

for clients with chronic diseases and disabilities. It

is thus suitable to provide a framework for determin-

ing functional capacity and developing exercise strat-

egy in persons with chronic diseases and/or disabil-

ities. The basic principles for exercise testing and

training stated provides the foundation for program

design. However, some special situations created by

a disease pathology, disability, or treatment alter these

basic principles. For example, exercise testing is an

important aspect of the approach used, but some peo-

ple will not have completed an exercise test before

starting an exercise program. Participation in regular

physical activity can enhance functional capacity, and

a primary goal is to get more individuals physically

active. Thus, for many people, exercise testing may

not be absolutely necessary before starting a low-level

physical activity program.

Many people who have chronic disease or disabil-

ity enter a downward spiral toward exercise intoler-

ance, so exercise intervention programs should be de-

signed to resist this spiral and optimize functional ca-

pacity. Within any given population, there is a wide

range of abilities determined by several factors; pro-

gression of the disease, response to treatment, and

presence of other concomitant illnesses. Expected

outcomes of exercise training are not always known.

Realistically, optimal exercise and medical program-

ming may yield improvements or merely prevent fur-

ther deterioration. There may be recommended tests

or programs that have not been validated, but that ex-

perience has shown to be successful. It is hoped that

optimal management will bring the individual greater

independence and improved quality of life.

In general, our society has a bias toward curative

rather than palliative medicine, toward making the

HEALTHINF 2017 - 10th International Conference on Health Informatics

478

disease go away rather than ﬁnding ways to cope with

disease. An unfortunate consequence of this perspec-

tive is that for persons with chronic disease or dis-

ability, we devalue the palliative beneﬁts of preserv-

ing functionality and well-being. Since the 1960s,

exercise has been promoted as a method of extend-

ing life, largely through prevention and moderation of

cardiovasculardisease. In recent years we discovered,

however, that perhaps the greatest potential beneﬁt

of exercise is its ability to strengthen musculoskele-

tal system structure and function, enhance function-

ing of cardiovascular, digestive and endocrine system

and to augment mental capacity through changes in

body chemistry. Its side effects unlike other pharma-

cological interventionsare positive (improvement and

preservation in functional capacity, freedom, and in-

dependence).

The frameworks and applications that cope with

the questions of health and wellness and that are avail-

able to the broad public audience are described e.g.

in (Banos et al., 2015; Joo et al., 2012; Laakko et al.,

2008).

3 SUPPORTIVE SOFTWARE

INFRASTRUCTURE

3.1 Software Requirements

Speciﬁcation

This section introduces a supportive software infras-

tructure for the exercise and wellness health strategy

framework. This infrastructurewill providemeans for

deﬁnition of the data collection procedure and data

collection itself, repository for storing and long term

management of health related data and metadata in

a standardizedway, data processing and interpretation

methods and/or deﬁned interfaces for the application

of data processing and interpretation methods. Last

but not least visualization tools providing views on

collected/analyzed data and their interpretations will

be included.

An important aspect of this supportive software

infrastructure is its wide range that includes collect-

ing data from classic measurements such as blood

pressure to relatively rare kinds of measurements such

as acquisition of brain frequencies or brain event re-

lated potentials. It means that also experience of

experimenters from the neuroinformatics lab (refer-

ence omitted for a review process) in measuring brain

waves highly contributed to the deﬁnition of the ﬁrst

set of collected health related human body parame-

ters.

Since big health related data (from at least thou-

sands of people) are planned to be stored in the reposi-

tory of this software infrastructure, the future analysis

of interdependence between brain parameter values,

other physiological and body proportion values and

personal lifestyle recordswould bring valuable results

for the targeted application of exercise and wellness

health framework strategies.

Thus the whole infrastructure will enable to ﬁnd

out complex information related to health conditions

of each participant and derive statistical results when

deﬁning various cohorts. With long-term and re-

peated measurements appropriate software modules

will be able to detect and depict personal trends and

changes in measured values.

However, the preliminary version of the soft-

ware infrastructure presented in this article (hereafter

called a software prototype) is required to help exper-

imenters to efﬁciently collect all health related data

and metadata outside the laboratory environment in

one session according to the procedure that could be

deﬁned even on site. The schema of such experimen-

tal procedure (that contains a limited set of measure-

ments) is depicted in Figure 1.

Figure 1: Experimental procedure.

The measured person starts with his/her registra-

tion, where he/she agrees with the collection and pro-

cessing of his/her personal and health related data (in-

formed consent) and provides basic information about

himself/herself (name, sex, age, etc.). After the regis-

tration he/she proceeds to ﬁll in a motivational ques-

tionnaire containing a set of 10-15 single choice ques-

tions related to his/her lifestyle. Then the measure-

ment cycle starts (as shown in Figure 1). Individual

Exercise and Wellness Health Strategy Framework - Software Prototype for Rapid Collection and Storage of Heterogeneous Health Related

Data

479

measurementsare grouped into sections depending on

measured parameters of human body. Every section

includes one or more physical sites where the exper-

imenter takes the measurement. When a single mea-

surement is completed, the acquired data are inserted

via a user interface into the system and sent to the

server. When the whole set of measurements is com-

pleted, the data are evaluated, sent back to the client

application and the participant can see his/her results

extended with additional information. The whole pro-

cedure shown in Figure 1 takes approximately 10–15

minutes.

The following list contains the current set of de-

ﬁned physical sites and health related data acquired at

these sites:

1. Brain

• P300 latency [ms]

• Fundamental frequency during concentration

[Hz]

• Fundamental frequency during meditation [Hz]

2. Body proportions

• Height [cm]

• Weight [kg]

• Muscle mass [kg] or [%]

• Body fat [kg] or [%]

• Body water [kg] or [%]

• Body Mass Index (BMI)

3. Electrocardiography (ECG)

• Heart rate [BPM]

• ST segment [ms]

• QRS complex [ms]

4. Blood pressure

• Heart rate [BPM]

• Systolic pressure [mm Hg]

• Diastolic pressure [mm Hg]

5. Blood sugar

• Concentration of glucose [mmol/l]

6. Spirometry

• FVC (Forced Vital Capacity) [l]

• FEV1 (Forced Expiratory Volume in 1st sec-

ond) [l]

• PEF (Peak Expiratory Flow) [l/s]

7. Hand reaction time

• Average reaction time [ms]

• Number of falsely pressed buttons

• Number of missed buttons

8. Leg reaction time

• Average reaction time [ms]

• Best reaction time [ms]

• Worst reaction time [ms]

• Standard deviation [ms]

9. Flexibility

• Difference between ﬁngers and foot during

deep forward bend [cm]

10. Color vision

• Number of wrongly recognized pseudoisochro-

matic tables

The whole software infrastructure as well as the

current software prototype is designed in a way that

allows easy enrollment of any future health related

data category, it means with any new collection of

health related data and metadata that could be de-

ﬁned even on site (just before the measurement). This

put further requirements on the ﬂexibility of the data

model itself and the technologies used for its repre-

sentation.

The software prototype can work in the online (de-

fault) or ofﬂine mode. When it is connected to the

Internet, it sends all input data directly to the main

server and receives back results and additional data.

When the Internet connection is not available, the pro-

totype switches to the ofﬂine mode. In this mode all

data are stored to a local repository and sent to the

server immediately when the Internet connection is

again available.

The parametric requirements on the prototype ap-

plication include its performance (input of health re-

lated data does not produce any visible delay), mobil-

ity (application can be used outside laboratory con-

ditions when several hundreds people are measured

during a day), simplicity and user friendliness (exper-

imenters are able to work with the application after

ﬁve minutes of training in the worst case).

3.2 Architecture and Design

The architecture of the software prototype is shown

in Figure 2. It follows the MVC architectural pattern

and client server architectural style.

The functionalities are encapsulated in modules

that can be added as plugins.

• The General module covers functionalitiesafford-

able also for non-logged users.

• The Admin module serves for the administration

of users and application setting.

• The Auth module is responsible for user registra-

tion and login.

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480

Figure 2: Software prototype architecture.

• The Measurement module includes deﬁnition of

measurement procedure and overall data manage-

ment.

• The Experiment module provides features for

adding, editing and deleting experiments.

• Every experiment needs own equipment for mea-

suring devices. The Equipment module stores

them in the database and provides tools for their

management.

• The QR generator module generates QR codes

into a PDF document given to the participant.

Each person has his/her number identiﬁer in-

cluded in his/her QR code.

• The Statistics module currently includes a func-

tion for simple statistics of reaction time.

Rest API is deﬁned for collecting data from client

devices.

3.3 Implementation and Deployment

The software prototype has been written in Python 3

language and uses the Flask micro framework that is

based on the Werkzeug toolkit and Jinja2 template en-

gine. The used languages and technologies include

Python, HTML5, CSS3, Flask, Sqlalchemy, and Post-

gre SQL.

The Postgre SQL database is used for storing data.

As a representative of open source object-relational

database system it offers signiﬁcant support for stor-

ing and retrieving JSON documents. Object relational

mapping is provided by the SqlAlchemy framework.

The current ERA model of the software prototype is

shown in Figure 3.

The application is hosted by a virtualized server

having the technical parameters provided in Table 1.

The web server NGINX listens on two ports (the

ﬁrst port is used for the release version and the sec-

ond one for the development version). NGNIX ex-

tends HTTP requests for non-standard headers CORS

(cross-origin resource sharing) technology which is

important for communication with mobile devices.

NGINX passes requests to the python application

with FastCGI protocol by a socket. Both development

and release versions run ﬁve instances. The process

describing how the requests are handled by the server

is shown in Figure 2.

Table 1: Server hardware and software speciﬁcations.

Processor

Intel(R) Xeon(R) CPU

E5-4620 v2 @ 2.60GHz

Memory 8036MB

Hard disk capacity 100GB

Operating system

Debian 8.4 with kernel

2.6

Web server

NGINX 1.6.2

Database Postgres 9.4

Language and tech-

nologies

Python 3 using frame-

work Flask

3.4 Testing

The software prototype has been tested on 346 people

in real environment (e.g. Days of science and tech-

nologies that were held in large tents on the square)

Exercise and Wellness Health Strategy Framework - Software Prototype for Rapid Collection and Storage of Heterogeneous Health Related

Data

481

Figure 3: ERA model.

and has been continuously improved according to op-

eration difﬁculties.

The list of devices which were used during the

testing is shown in Table 2. The control software for

impact dance is described in (omitted for the review

process).

Table 2: Used devices.

Site Device name

Body proportions

Medisana BS 440

Connect

Electrocardiography

ReadMyHeart Hand-

held ECG

Blood pressure

Omron M6 Comfort

Blood sugar

FORA Diamond

Mini

Spirometry SP10W

Hand reaction time

Device for cognitive

research

Leg reaction time

Impact Dance Pad

Flexibility Podium and ruler

Color vision

Pseudoisochromatic

tables

4 CONCLUSIONS

In this paper we presented an idea of the exercise

and wellness health strategy framework and the ﬁrst

steps that were done to support this framework by an

appropriate software architecture. The proposed and

developed software prototype covering a part of the

whole infrastructure, namely rapid collection, stor-

age and visualization of heterogeneous health related

data, was successfully tested on more than three hun-

dreds participants outside laboratory conditions.

The presented software prototype enables its users

to quickly set the health related data to be collected

and the whole data collection procedure. Then the

data are collected, stored and visualized in an efﬁcient

way. Currently the prototype enables not only col-

lection of classical data, but also non-traditional data

(such as brain data) gathering. The software proto-

type design follows proven architectural patterns and

styles, its modular structure facilitates its further ex-

tension.

In the future work we will focus on continuous ex-

tension of the software prototype to cover other parts

of the intended software infrastructure for exercise

and wellness health strategy framework. This include

e.g. the modules for food and exercises recommenda-

HEALTHINF 2017 - 10th International Conference on Health Informatics

482

tions, overall data evaluation or improved data visual-

ization.

ACKNOWLEDGMENTS

This publication was supported by the UWB grant

SGS-2016-018 Data and Software Engineering for

Advanced Applications, the project LO1506 of the

Czech Ministry of Education, Youth and Sports under

the program NPU I and the 2nd Internal grant scheme

of UWB School of Computing, 2016.

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