Motor Rehabilitation and Biotelemetry Data Acquisition with Kinect

Francisco Marcelino Almeida de Ara

ujo

1 a

, Paulo Roberto Ferreira Viana Filho

1 b

Jesus Abra

ao Adad Filho

1 c

, Nuno M. Fonseca Ferreira

2,3 d

, Ant

onio Valente

3,4 e

and Salviano F. S. P. Soares

4,5 f

Federal Institute of Piaui, Teresina, Brazil

ISEC - Institute of Engineering of Coimbra, Portugal

INESC-TEC Technology and Science, Portugal

University of Tr

as-os-Montes and Alto Douro, Portugal

IEETA - UA, Portugal

Keywords:

Rehabilitation, Kinect, Disabilities, Biotelemetry, Movement.

Abstract:

Accessibility and inclusiveness of people with disabilities is a recurring theme that is already perceived as an

issue in the ﬁeld of human rights. Ramps, elevators, among other devices aim at the inclusion of these indi-

viduals with limited mobility. Various types of motor limitations, specially partial limitations, are linked to

corresponding physical-motor rehabilitation process, with the purpose of reducing or eliminating the patient’s

dependence on a caregiver or devices for adaptation. Patients with motor disabilities must practice physio-

therapeutical exercises along a physician in order to perform body and muscle analysis to ensure the patient’s

well-being. To reach a more accurate analysis, physiotherapists use a range of devices to acquire patient data,

such as the spirometer, to acquire the patient’s breath intensity and lung capacity. Similarly, there are other

technologies capable of acquiring motion data and quantifying them. This work aims to develop a system that,

paired together with an exercise game project (exergame), can acquire and transmit the motion data acquired

in-game for an easier and faster analysis of the patient’s growth, relying on graphs, tables, and other visual

indicators to improve the evaluation of physiotherapeutic treatments. The usage together with an exergame

also has beneﬁts such as increased patient compliance with the treatment and improvements in well-being.

1 INTRODUCTION

Present as one of the strongest entertainment indus-

tries(Cummings, 2007), videogames have evolved

over the decades in many forms since its ﬁrst appear-

ance in 1958 with Tennis for Two. Many of its im-

provements are reﬂected in the way the player is able

to input commands in order to play the game, ranging

from simple button presses to the usage of complex

technology. In order to innovate and gain their con-

sumer’s attention to buy their game consoles, some

companies invest in the way the player is able to in-

teract with the game and input these commands. One

https://orcid.org/0000-0001-8928-0077

https://orcid.org/0000-0002-4185-0613

https://orcid.org/0000-0001-6372-5541

https://orcid.org/0000-0002-2204-6339

https://orcid.org/0000-0002-5798-1298

https://orcid.org/0000-0001-5862-5706

of the most known and successful examples is Nin-

tendo’s Wii, which used motion capture technology

as a form of controlling the game.

Motion capture technologies are not limited only

for entertainment purposes, however. For example,

the Wii was used for physiotherapeutic rehabilitation

in Parkinson’s disease patients, where it was relevant

to the treatment as a supplementary activity, named

Wii-hab(Herz et al., 2013).

Interfaces that have human-computer interac-

tions that involve human motion, such as Nintendo

Wii

controllers, are known as Natural User Inter-

face (NUI). Another strong example of NUI usage

is the Kinect

, which uses only sensors to acquire

data and does not require any controller in the player’s

hand, unlike the previous case. That’s why it has be-

come a revolutionary (Martin-SanJose et al., 2017)

device for the video game industry. Like the Nin-

tendo Wii and other NUI devices, Kinect has also

been widely used for therapeutic purposes (Szykman

242

Araújo, F., Viana Filho, P., Adad Filho, J., Ferreira, N., Valente, A. and Soares, S.

Motor Rehabilitation and Biotelemetry Data Acquisition with Kinect.

DOI: 10.5220/0009157202420249

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 1: BIODEVICES, pages 242-249

ISBN: 978-989-758-398-8; ISSN: 2184-4305

et al., 2015)(Da Gama et al., 2015)(Dehkordi et al.,

2018), where it has gained notoriety in projects in-

volving stroke patients (Robertson et al., 2013)(Hsieh

et al., 2014)(Dukes et al., 2013), cerebral palsy,

Parkinson’s disease, people with cognitive disabilities

(Nazirzadeh et al., 2017), among other conditions that

limit physical movement.

2 JUSTIFICATION

There are about 46 million individuals in the Brazil-

ian territory. About 24% of the population claim to

have some form of disability, which may cause dif-

ﬁculties in performing many essential tasks of daily

life. Approximately 7% of the population declares

to have some motor disability that indeed causes dif-

ﬁculties in this type of tasks. Keeping that data in

mind and the various diseases and illnesses that lead

to these disabilities, it is possible to observe in many

situations that the systems designed to promote acces-

sibility to persons with disabilities are neglected and

often inoperative when they exist.

Research for motor disability treatment and reha-

bilitation commonly comes across a problem: An ap-

plied solution to one condition does not necessarily

work for another, even if similar. There is even the

possibility that solutions that could be successfully

applied to one patient may not serve another with the

same limitation. This could be due to different factors

such as the disease itself, the severity of each case,

and the area of the body affected. Thus, meeting this

demand for solutions for each case can become an ar-

duous and laborious task.

The beneﬁts of physical therapy treatment for pa-

tients are many: (Costa et al., 2005) mentions, for ex-

ample, that an individual’s ability to stand up from

a wheelchair decreases their dependence on a care-

giver and reduces or eliminates problems deriving

from the condition, such as blood clots, muscle at-

rophy, bladder and urinary tract infection, and osteo-

porosis. More beneﬁts are also seen in the psycholog-

ical part, with an improvement in the patient’s self-

esteem, family and social relationship, directly re-

ﬂects on treatment.

3 TECHNOLOGY AND

VIDEOGAMES IN MOTOR

REHABILITATION

The employability of video games for physiothera-

peutic purposes is commonly researched in the aca-

demic ﬁeld through the gamiﬁcation of activities used

in the treatments. According to (Hamari et al., 2014),

gamiﬁcation can be deﬁned as a process that aims to

improve a service through motivational gains, creat-

ing game-like experiences. For the treatment of a

patient, a variety of technologies can be employed,

aside from commercial video game consoles aimed

at home use and commonly for entertainment pur-

poses. Since rehabilitation activities and exercises

aim to stimulate patient movement, the technologies

employed are usually reactive to the user’s movement

or action, such as the use of pressure sensors and sen-

sors that calculate the individual’s breathing strength

in lung exercises. NUI tools are included in this range

of applied technologies. They ensure user interaction

with the computer, which responds appropriately.

Game-creating software tools known as Game En-

gines provide the ability for people or groups to create

their own custom games. In combination with NUI

tools such as Kinect, this makes it possible to cre-

ate solutions that address both the treatment of peo-

ple with disabilities and the accessibility of players

with motor disabilities when using these devices. A

great example is Kinect Wheels(Gerling et al., 2013),

which used the C# library provided by the manufac-

turer, Microsoft, to create gestures so that wheelchair

users can replace movements they can’t do.

4 BIOTELEMETRY AND DATA

ACQUISITION

One aspect that can be explored for understanding

a patient’s situation regarding their treatment is data

acquisition. The act of acquiring measurements and

data at a distance is known as Telemetry (Cooke

et al., 2004). In turn, Biotelemetry represents the use

of this data acquisition within biology, medicine, and

health to acquire patient data such as vital signs (Kim

and Cho, 2001). An example of using biotelemetry

is to acquire and store a person’s heart rate, possibly

giving an alert when there is an abnormality.

(Cooke et al., 2004), in a paper analyzing

biotelemetry as a research tool for animals and

ecosystems, saw immense potential for researchers.

In humans, biotelemetry can be used as a means of

monitoring rehabilitation patients, like acquiring a pa-

tient’s heart rate while performing a rehabilitation ex-

ercise(Kim and Cho, 2001). It can also be used to

check any abnormalities in an elderly person’s body

in case of emergency at home(Penhaker et al., 2007).

The data acquisition that biotelemetry provides

can be useful as an auxiliary tool in motor rehabilita-

tion exercises. Acquiring numerical data during treat-

Motor Rehabilitation and Biotelemetry Data Acquisition with Kinect

243

ment helps to measure, for example, treatment effec-

tiveness over time by comparing treatment initiation

data and the most recent data.

A project currently under development (Anto-

nio Valente, 2019) uses the Unreal Engine 4 game en-

gine to create a Kinect application that seeks to save

and display the time a patient takes to touch an ob-

ject when prompted. The intention of the project is

to analyze and provide data on the movement of a pa-

tient with motor disabilities, as well as allowing the

customization of the exercises as the physiotherapist

needs.

By analyzing the time it takes for a patient to per-

form a simple task, such as grasping an object in front

of him, it is possible to infer from real data the per-

formance and effectiveness of the treatment. In the

physiotherapeutic environment, the method used for

measurements and evaluations are dynamic, where

professionals make judgments according to observed

data and their experience (Gil, 2015). By receiving

the patient’s data via biotelemetry, it is possible to

obtain a more accurate and less empirical treatment

analysis, avoiding interpretation problems if, for ex-

ample, the physical therapist responsible for a patient

is changed. In the event of a change, the report left by

the previous manager may be interpreted differently

from the intentional one by the new physical thera-

pist. Given this, a system for managing this data can

prove to be a useful tool to remedy these and other

problems.

An online system enables quick and convenient

analysis of treatment data from anywhere, whether by

the physiotherapist or the patient himself. Depending

on the types of data that are obtained during the ses-

sion, they can be updated immediately after the ses-

sion ends for consultation. If the data is more complex

or needs longer treatment, the patient can be informed

and access the results online at home.

5 TIME-OF-FLIGHT CAMERAS

In order for data to be acquired from a patient’s body,

a sensor must be employed depending on the type of

data sought. For example, to obtain a patient’s heart

rate data, an electrode is placed to receive the signal.

Similarly, to acquire data from a person practicing

physical therapy exercises it is necessary that a sensor

that obtains the individual’s movements be connected

to obtain the movements for the computer.

The motion capture process, also known as Mo-

Cap is performed, according to Vital et al.(Vital et al.,

2017), acquiring the body segments’ acceleration, ve-

locity, time and position of an individual. This data

can be measured using specialized sensors that can

acquire them in different ways depending on the tech-

nology employed. In her work is also shown the dif-

ferent methods and apparatus for the acquisition of

this data, as well as their advantages and disadvan-

tages.

Time-of-ﬂight cameras are optical devices that

have the ability to detect their surroundings by calcu-

lating the time light takes to reach an object and return

(Mutto et al., 2012). An example of using this tech-

nology is the later version of Kinect

(Kinect V2),

also mainly used in the digital gaming business. Un-

like depth cameras, they offer 3D images at a good

frame rate per second (also called FPS), also bringing

a depth gauge for each pixel of the scenario (Vital,

2015). Although intended to be used as a form of con-

trol for digital games, it is a tool that produces, even

in its ﬁrst version, acceptable results, but inferior to

a Vicon

passive marker system, for example(Dutta,

2012).

Their advantages and disadvantages(Vital, 2015)

are:

Advantages: Depth at each pixel with high fram-

erate; light weight; small and compact design; self

lighting; and reduced power consumption. Disadvan-

tages: Susceptibility to illumination; Multiple reﬂec-

tions - ToF cameras illuminate an entire scene; and

interference. That means that if multiple ToF cam-

eras are running at the same time, they may disturb

each other’s measurements, depending on multiplex-

ing time and modulation frequencies.

With its approximate price of $200, it is greatly

advantageous compared to other tools available on the

market.(Steward et al., 2015).

How to choose which equipment to use is a crit-

ical topic that underpins the development of a motor

rehabilitation solution for patients. To achieve good

results, you should consider the following aspects of

the tool: Price; Data capture quality; Market acces-

sibility; and value in money.

Comparing the tools currently available to each

other is essential to understanding each one’s

strengths and weaknesses. This comparison proce-

dure is called Benchmarking.

Vital et al.(Vital, 2015) for example, benchmarks

the main aspects of the tools available in the market,

comparing with the proposed solution in her work:

the FatoXtract

Using the data raised by Vital et al.(Vital, 2015)

and through analysis of the results of the review ar-

ticles presented by Da Gama et al.(Da Gama et al.,

2015), Szykman et al.(Szykman et al., 2015), and

Dekhordi et al.(Dehkordi et al., 2018), it is noticed

that the Kinect is able to detect and replicate user

BIODEVICES 2020 - 13th International Conference on Biomedical Electronics and Devices

244

movements in a portable way, achieving good results,

and costing less than 10% of the value of the other

high-end tools.

Between the Kinect V1 and V2 cameras, which

have a low price difference, the most reliable and

recent one is the Kinect V2 for Xbox One

, us-

ing time-of-ﬂight technology to map the body and

ensuring better performance. The responsible com-

pany (Microsoft) offers a developer tools package,

also known as Software Development Kit (SDK), al-

lowing the tool not only to be used for MoCap, but for

anything the developer may need to create an applica-

tion.

About the accuracy of the data acquired,

Dutta(Dutta, 2012) reports that Kinect V2 has accept-

able accuracy, but less than that of a Vicon system by

at least one degree of magnitude. It also reports that

some may choose to sacriﬁce some accuracy in ex-

change for portability. Another point to note is the

availability of Kinect, which can be purchased online

or in physical stores with little effort and few inven-

tory or delivery issues.

6 OBJECTIVES

6.1 General Objectives

Seeking a better quality of life for people with phys-

ical disabilities, this work seeks to create a tool that

demonstrates the acquisition of data from patients un-

dergoing motor rehabilitation. The purpose of this

project is also to help standardize the evaluation of

acquired data and give both patient and physiothera-

pist support and convenience in accessing this data.

6.2 Speciﬁc Objectives

This work aims to produce a software using the

Django platform and its libraries to program in

Python language an API (Application programming

interface) that will perform data acquisition, stor-

age and request operations using the Django REST

Framework library. Along with the API, an applica-

tion, also in the same Django project, must be created

as an interface for navigating its users who wish to

view the data.

Data acquisition should be done through a pre-

existing application(Antonio Valente, 2019) made us-

ing Unreal Engine 4.20 integrated with Kinect V2 and

its computer adapter. This application is responsible

for acquiring patient movement data and communi-

cating with the Django API via the VaREST plugin

for requesting, packaging, and sending data in JSON

format.

7 THEORETICAL BASIS

Several researchers have conducted studies in the area

of motion capture. Many use motion capture tools for

healthcare applications, and others research their use

to automate processes with gesture recognition.

Despite being a fairly recent technology, many

applications and research have already been done

achieving great results. The result of these researches

were works that generated important data for the cre-

ation of this article.

The increasing use of motion capture technol-

ogy, as previously mentioned, has grown signiﬁcantly

since its ﬁrst appearances and public availability, es-

pecially in healthcare and medicine. With this growth,

a review article is necessary for a better follow-up of

these results obtained in the academic and scientiﬁc

community. Szykman(Szykman et al., 2015), Dehko-

rdi(Dehkordi et al., 2018), and Da Gama(Da Gama

et al., 2015) conducted research including the use of

Kinect for physical therapy rehabilitation, including

patients with autism, cerebral palsy, multiple sclero-

sis, and stroke, among other conditions.

Dehkordi et al.(Dehkordi et al., 2018) explore

the use of applications with Kinect, demonstrating

in some of the results the successful use of the tool

with patients with autism, children with psychologi-

cal or emotional disorders and their monitoring. Most

studies included in the research refer to stimulating

physical movements and motor skills, some relying

on some kind of gesture recognition for functioning.

Dehkordi et al. points out that the research and

its implementation are partly employed in the school

environment or at home, but according to the results

obtained, the use of the Kinect system can also be ap-

plied in many other environments, including hospitals

and clinics, where new applications are being devel-

oped and tested.

However, some limitations on Kinect were discov-

ered during the analysis:

• Limitation on movement capture of participants

due to lack of space;

• The height of adult participants and objects be-

tween player and researcher or Kinect does not

allow the system to correctly detect participant

movement;

• Kinect Systems Unable to Support Multiple Dis-

abled Participants

Motor Rehabilitation and Biotelemetry Data Acquisition with Kinect

245

• The Kinect sensor must be ﬁxed in one place, and

has a range of around ten meters, meaning that

the movement should occur only in front of the

sensors.

In addition, the study proves a beneﬁcial relation-

ship between Kinect systems and training games, and

ﬁndings that suggest facilities for caregivers such as

teachers, therapists, physicians, and family members.

Szykman et al.(Szykman et al., 2015) expresses

how video games have strayed from being not just en-

tertainment gadgets, but also valuable tools that, using

Natural User Interface (NUI), could be used to heal

and treat metabolic, neurological, and vascular com-

plications.

The authors use a automatic search system to

acquire data and keywords from various scientiﬁc

databases. It was found that research involving the

development of games for people with disabilities is

increasing, as well as reporting signiﬁcant improve-

ments in patients’ well-being and the data doctors can

obtain to conduct a better treatment

One of the clearest beneﬁts found was the motiva-

tion generated by games and applications that persist

during treatment, where many researchers take advan-

tage of this element as a way to enhance the treatment

performed.

8 METHODOLOGY

For the creation of a software that fulﬁlls its intended

purpose, a mechanism for storing and manipulating

data is seen as a key to its operation. To achieve

this functionality, the Django platform was used along

with the Django REST Framework plugin to develop

a system that has the ability to function online. Work-

ing online is also an essential attribute for the most

convenient display of this data to the target audience,

ie physiotherapists and patients, enabling them to ac-

cess the data at any time.

For a demonstration of the data that the sys-

tem can manage, this software will initially process

the data obtained from the previous project at Un-

real(Antonio Valente, 2019), which will be developed

along with the program described in this work. The

software (called ’KinectAPI’) consists of a Django

project with a single app called ’kinect’

Using Django and the Django REST Framework

plugin, you able to create an API that can create, store,

and display custom objects in a database. This means

that we can abstract real data into a form that the sys-

tem understands and is free to manipulate. In Django,

these entities are abstracted to objects of a model.

Therefore, we can think of a physiotherapist as an

object model that has important data from the actual

physiotherapist. This object would have, for example,

the name of the physiotherapist, his clinic, his CRM

(Brazilian Physician Credentials), e-mail, telephone

number, among other relevant data.

Like the physical therapist, other entities need to

be abstracted before they can be stored. These other

entities also need to be relevant in the treatment aspect

of the patient. Are they:

• Physiotherapist;

• Patient;

• Treatment;

• Treatment Session;

• Exercises;

• Time.

In Django, to implement this abstraction, you need

to create a model for each of these entities. With mod-

els created in the ’models.py’ ﬁle, Django itself gen-

erates the database automatically for immediate use.

Models, like their real entities, have relationships

with each other. For example: A treatment is made

up of a physical therapist, a patient, and has a series

of sessions of an exercise. All of these relationships

must be represented and implemented as per the ac-

tual cases. These relationships can most easily be

seen in the class diagram:

Figure 1: Class Diagram.

Having now all models put and associated as

needed, now you have to create and manipulate this

data. For the correct registration of objects, an initial

interface is required before they can be created. This

can be done through Django’s Forms, coupled with a

View class and an HTML website template.

Views in Django are responsible for managing re-

quests for the software and their responses to each.

In this case, it displays the site with the data to be

ﬁlled in by the user, and when submitting, properly

acquires and processes the data received. With this,

we can create a screen for the user to register, be it a

patient or a physical therapist.

BIODEVICES 2020 - 13th International Conference on Biomedical Electronics and Devices

246

Figure 2: Register screen.

Like the registration screen, a login screen has

been implemented. With registered users, they must

be given actions that can be performed with the data.

These actions should also include the registration of

subsequent objects, exercise and treatment. And en-

compassing all the necessary actions, you can create

a use case diagram:

Figure 3: Use case Diagram.

The physiotherapist must be able to perform all

necessary operations before using the application on

Unreal. Therefore, he/she should ﬁrst register the

treatment, with all necessary data, including the pa-

tient’s id (can also be selected from a list of patients)

and the prognosis of the problem to be solved. After

the treatment has been registered, the Unreal applica-

tion may be used.

To perform the exercise in the application, the

physiotherapist must enter the username and pass-

word along with the registered treatment ID. Thus, it

is not necessary to enter patient data or write about

the prognosis, all these data were previously entered

and processed. As soon as the physiotherapist enters

the required data, he is taken to a menu screen where

the corresponding exercise can be selected.

Any operation involving data transfer between the

application in Unreal and the Django API is per-

formed through JSON requests. The API has a se-

ries of URL addresses where the application can make

these requests to perform a desired operation. When

logging in, for example, the credentials obtained are

Figure 4: Training selection screen.

registered and sent to the API. It then checks the en-

tered credentials and, if authorized, returns a Token.

This token is stored so that it can be used in place

of the username and password for subsequent opera-

tions.

Once the exercise is selected, a session is created

and assigned to the treatment whose id was provided,

along with the exercise date, time, and name. Times

are sent each time the patient touches an object when

asked. In the Unreal app, the exercise is performed

from a series of static objects ﬂoating over the patient,

all semi-translucent in color, which turn golden when

the patient must move and stretch to reach them. Only

one of the objects activates and turns golden at a time.

At touch, the name of the touched object as well as the

limb used to touch are sent to the database. Like login,

session creation and time recording are also requests

with JSON.

With the interaction between the two systems im-

plemented, it now remains to create an interface for

users to see the data acquired, and in the case of the

physiotherapist, create and manage this data. In the

Django API itself it is possible to provide this inter-

face in the same way as the register. A view is created

to manage each operation made. When logging in, the

user must have operations available in a menu accord-

ing to their type: Physiotherapist or Patient.

The patient can check his treatments in a list,

and check each exercise session, from the same point

of view of the physiotherapist. The physiotherapist

has more operations, such as recording a treatment,

adding an evaluation to a treatment, recording a new

exercise, among other views that can be seen in the

use case diagram (Figure 3).

After selecting a treatment, information about it

can be viewed on the screen as either a small table

sorted with the time taken to perform the exercise ac-

tion and the limb used.

As in the session details, a graph is also shown

when selecting a treatment, with performance data per

session. All graphs are generated using the Graph.js

extension, enabling automatic generation of an inter-

active graph using the JavaScript language. These

Motor Rehabilitation and Biotelemetry Data Acquisition with Kinect

247

Figure 5: Performance Graph per Limb (Right/Left Arm).

Figure 6: Performance Graph per Session.

charts can display or omit information according to

your user’s needs. So if the user wishes, only one or

all sessions can be displayed at a time.

9 CONCLUSIONS

From the results obtained from the integration be-

tween the two platforms, it is possible to demonstrate

the ability of both systems to communicate and ex-

change information with each other, enabling the ac-

quisition of patient movement data through the Un-

real application and the processing and display of data

obtained using a Django system. In addition to com-

municating and receiving application information, the

API is also capable of using graphical systems and ta-

bles for proper data display, facilitating and ensuring

better and faster understanding by both the physio-

therapist in charge and the patient that wants to check

their own performance.

9.1 Testing with Wheelchair Users

As stated by Da Gama(da Silva et al., 2007), a com-

mon problem seen in many studies related to motor

rehabilitation with Kinect is the lack of actual patient

testing. However, for successful and properly tested

tests, the approval and follow-up of the Brazilian Re-

search Ethics Committee (CEP) with human beings

is required and to be in accordance with international

ethical guidelines (Declaration of Helsinki, Interna-

tional Guidelines for Biomedical Research involv-

ing Human Beings - CIOMS) and Brazilian (Resolu-

tion CNS 466/12 and complementary). This follow-

up process requires an extensive process that takes

months to complete before testing procedures.

That said, during project development, the objec-

tives and prototypes were delivered and tested with

one person, both wheelchair user and physical ther-

apy professional. During the tests, exercise proto-

cols were presented and the data acquisition proposal

validated, besides participating in proposed exercise

sessions. However, for more extensive research with

more concise data, more physical therapists and vol-

unteer wheelchair users are required, which again re-

quires the presence of the Research Ethics Commit-

tee.

10 FUTURE WORKS

With both functional systems in hand, there remains,

in addition to wheelchair research and testing, the im-

provement of the exercises to be used and their ap-

plication to different parts of the body and in dif-

ferent environments. Another progress to be imple-

mented in the project is the expansion of data obtained

via biotelemetry and its processing, which may range

from the patient’s heart rate to the angle of the limb in

interest.

Another necessary implementation is the direct

experimental use of the system in a hospital environ-

ment and in physiotherapy clinics, for a better anal-

ysis of the strengths and weaknesses of the system

and their appropriate corrections. With appropriate

changes made, the system should be retested until it

is ready for actual use in rehabilitation clinics.

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