Measurement of the Reaction Time in the 30-S Chair Stand Test

using the Accelerometer Sensor Available in off-the-Shelf Mobile

Devices

Ivan Miguel Pires

1,2,3

, Diogo Marques

, Nuno Pombo

1,3,5

, Nuno M. Garcia

1,3,5

, Mário C. Marques

4,6

and Francisco Flórez-Revuelta

Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal

Altranportugal, Lisbon, Portugal

ALLab - Assisted Living Computing and Telecommunications Laboratory, Computing Science Department,

Universidade da Beira Interior, Covilhã, Portugal

Department of Sports Sciences, Universidade da Beira Interior, Covilhã, Portugal

Universidade Lusófona de Humanidades e Tecnologias, Lisbon, Portugal

Research Centre in Sport, Health and Human Development, Covilhã, Portugal

Department of Computer Technology, Universidad de Alicante, Alicante, Spain

Keywords: Reaction Time, Accelerometer, Mobile Devices, 30-S Chair Stand Test, Elderly People.

Abstract: The 30-s Chair Stand Test (CST) is commonly used with elderly people for assessing the lower limbs

strength, which can provide sufficient information regarding the general mobility and fall risk. The mobile

devices are widely used for the acquisition of the different physical and physiological data from the sensors

available, including the accelerometer. In this way, the aim of the present study consisted on the

development of an automatic method for the measurement of the reaction time (RT) based on the 30-s CST

using a mobile device. Besides that, the data acquisition through an accelerometer allows the assessment of

different variables, such as the maximum values of the acceleration, the instant velocity, the maximum force

and the peak power, that may contribute to a better understanding of the physical demands during the 30-s

CST performance. The results presented in this study demonstrated that the calculation of the RT and the

different variables during the 30-s CST performance is possible, opening new possibilities for the

development of scientific projects, namely those that encompasses the motor and cognitive training of

elderly people.

1 INTRODUCTION

The ageing process involves several transformations

within the human body, including a decline of the

skeletal muscle tissue, described as sarcopenia

(Walston, 2012), and a decrease in the cognitive

function. Thus, contributing to a slower processing

speed and motor performance (Bautmans et al.,

2011), and an increased reaction time (RT), both in

elderly people with and without cognitive

impairments (Arnold et al., 2015).

According to Wong, Haith, and Krakauer (2015)

the RT means the time from the stimulus onset to the

beginning of the motor action. It includes the time to

capture the stimulus, process the information and

initiate a motor response (Bautmans et al., 2011). It

is current practice to evaluate the RT through a

visual and/or an acoustic stimulus either from a

computer software (Jain, Bansal, Kumar, & Singh,

2015) or mobile devices (Mulligan, Arsintescu, &

Flynn-Evans, 2016). The latter are equipped with

several sensors, e.g., Global Positioning System

(GPS) receiver, gyroscope, accelerometer,

magnetometer, and microphone, which enable the

acquisition of different types of data, including those

related to physical activities.

Following previous work regarding the

development of methods for the acquisition of

physical and physiological parameters using off-the-

shelf mobile devices, a method for the measurement

of the jump flight time was previously developed by

Pires, Garcia, and Canavarro Teixeira (2015), as

well as a method for the recognition of Activities of

Pires, I., Marques, D., Pombo, N., Garcia, N., Marques, M. and Flórez-Revuelta, F.

Measurement of the Reaction Time in the 30-S Chair Stand Test using the Accelerometer Sensor Available in off-the-Shelf Mobile Devices.

DOI: 10.5220/0006813102930298

In Proceedings of the 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2018), pages 293-298

ISBN: 978-989-758-299-8

293

Daily Living (ADL) and their environments (I. Pires,

N. Garcia, N. Pombo, & F. Flórez-Revuelta, 2016;

Pires, Garcia, & Flórez-Revuelta, 2015; I. M. Pires,

N. M. Garcia, N. Pombo, & F. Flórez-Revuelta,

2016).

The development of systems aimed to

monitoring the lifestyle is an emerging topic,

included in the Ambient Assisted Living (AAL) and

Enhanced Living Environments (ELE) systems

(Botia, Villa, & Palma, 2012; Dobre,

Mavromoustakis, Garcia, Goleva, & Mastorakis,

2016; Garcia, Rodrigues, Elias, & Dias, 2014).

The evaluation of the physical fitness in elderly

people is usually done through the Senior Fitness

Test (SFT), which is a battery of 7 tests developed

by Rikli and Jones (2001). One of the tests, the 30-s

Chair Stand Test (CST) is used to assess the lower

body strength, enabling also to detect changes in

mobility and fall risk (Pereira et al., 2012). In the

literature, there are several studies that used the

accelerometer in the 30-s CST to assess the physical

condition of elderly people (Millor et al., 2017;

Regterschot et al., 2014). . The accelerometer sensor

allows the measurement of different real-life

situations and includes the concept of the

development of a personal digital life coach, which

can be adapted to monitoring the physical activity of

elderly people (Garcia, 2016). This sensor have been

successfully implemented in different tests and age

groups, like the Time-Up and Go (Reis, Felizardo,

Pombo, and Garcia, 2016) and the Heel-Rise Test

(Pires, Andrade, Garcia, Crisóstomo, and Florez-

Revuelta, 2015).

Nevertheless, to the best of our knowledge, the

measurement of the RT in the 30-s CST using the

accelerometer sensor available in off-the-shelf

mobile devices is not yet implemented. Thus, the

aim of our study is to develop an automatic method

to measure the RT based on an acoustic stimulus in

elderly subjects, performing the 30-s CST. Besides

that, it is our intention to validate this protocol for a

future use on studies related to the effects of high-

speed resistance training on the velocity of the body

movement and the RT in elderly people.

This paragraph ends the introductory section.

Section 2 presents the methodology of this study.

The results are shown in the section 3 and discussed

in section 4. Finally, the conclusions are presented in

section 5.

2 METHODS

2.1 Study Design

For the measurement of the RT in the 30-s CST, we

developed an application for mobile phones that

acquires the accelerometer data during the

movement. A subject (68kg; 1.70m) volunteered to

be assessed on the 30-s CST using the mobile device

in the front pocket of the jeans for further calculation

of the RT. The subject repeated the test 3 times.

It is important to note that in future experimental

studies, this test protocol will be applied with elderly

people.

The present study is structured in three stages:

1. The development of a mobile application

for capturing the sensors' signal, with the

transmission of an acoustic signal (beep)

to initiate the 30-s CST.

2. The implementation of the 30-s CST to

evaluate the RT and the respective ability

based on an acoustic signal.

3. The analysis of different variables (i.e.,

velocity, force, power) based on the

accelerometer data.

2.2 Description of the Modified 30-S

CST

This test was originally designed by Jones, Rikli,

and Beam (1999). The test procedure consists in the

following:

In a sit position on a chair (next to a wall) with

the back straight and the arms crossed over the

chest, after a verbal permission (“1, 2, 3, go”), the

subjects had to stand up and sit down from a chair as

many times as possible within 30 s. In the present

study, the modification consisted in the introduction

of an acoustic signal (a beep), instead of a verbal

signal to initiate the test.

2.3 Data Acquisition

In the present study the off-the-shelf mobile device

used was a Huawei Y530-U00. This device has an

accelerometer sensor incorporated that acquires data

at 60 Hz frequency (Huawey, 2013). The data

acquisition was performed with a mobile

application, whose function is to save the outputs of

the accelerometer sensor into a text file for further

processing. The data were acquired with the off-the-

shelf mobile device placed in the front pocket of the

pants for the correct acquisition of the accelerometer

outputs.

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The data acquisition was started by pressing a

start button in the application with the subject sit and

not moving. After 10 s of the start, an acoustic signal

indicates that the subject should start the test and

data continues to be acquired for more 30 s.

2.4 Data Analysis

2.4.1 Data Processing

After the data acquisition process, the text files

stored in the mobile devices were processed in a

computer.

The accelerometer measures the three

components of the acceleration, but since it was not

possible to ensure that the device position remained

unchanged through the test duration, it was decided

to compute the total acceleration from the three

components.

In order to have the gravity acceleration value

when the subject is not moving, the following

correction was introduced (Bennett, Jafari, & Gans,

2014):





 



 



  (1)

where a

corr

is the corrected acceleration, a

meas

is the

acceleration measured, and a

ref

is a reference value

equal to the average value of the acceleration

measured in the 5 s previous to the acoustic signal

(i.e., starting of the test). This reference value was

needed since the signal presents small oscillations

even when there is no movement.

2.4.2 Calculation of the Sensor-based 30-S

CST Variables

After the data processing, and based on the

magnitude of the acceleration signal, the following

variables, presented in the Figure 1, were assessed:

1. Reaction Time (RT): the time between the

acoustic signal and the initiation of the

movement;

2. Movement Time (MT): the time from the

beginning of the motor action to the end of

the movement (i.e., return to the sit

position);

3. Total Time (TT): the time from the acoustic

signal to the return to the sit position.

In the present study the focus is on the RT

evaluation and therefore the analysis will be mostly

based only on the first stand up and sit down

movement of the several repetitive movements that

occur during the 30-s CST.

Figure 1: Signal Plot of the acceleration during the stand-

up phase from a sit position on the chair.

It is important to note that in future studies, for

example related to the influence of high-speed

resistance training programs on the RT in elderly

people, other variables can be assessed through the

accelerometer data, such as:

1. Maximum absolute acceleration;

2. Maximum absolute velocity

3. Mean velocity;

4. Maximum absolute Force;

5. Maximum absolute Peak power.

As a demonstration, we calculated those

variables, which can be seen in the results section.

The velocity was obtained by numerical

integration of the acceleration, for example using the

trapezoidal rule (Davis and Rabinowitz, 2007).

























 





 



(2)

where V is the velocity, a is the acceleration, t is the

time, and subscripts 1 and 2 correspond to previous

and actual time, respectively. The force was

calculated with Newton’s second law     



(Keller, 1987), where the relative acceleration is





 



  (Tao, 1967). The power is

simply      (Tihanyi, Apor, and Fekete,

1982).

3 RESULTS

3.1 Prototype

The mobile application developed for this study has

an easily usage adapted for elderly people, designed

for different ages, as presented in the Figure 2. The

usage of the mobile application consists only in

pressuring a large button enabling and stopping the

data acquisition. At this stage of the project, the

mobile application only performs the data

acquisition of the accelerometer data, but, in the

Measurement of the Reaction Time in the 30-S Chair Stand Test using the Accelerometer Sensor Available in off-the-Shelf Mobile Devices

295

future, the calculation of the RT and the other

variables should be calculated at real time within the

mobile application. The files created by the mobile

application are stored in the mobile device for

further processing and validation.

Figure 2: Prototype of the mobile application developed.

3.2 Validation

The relative acceleration is presented in Figure 3.

The instant velocity is represented in the Figure 4.

The maximum force produced during the stand up

phase was also calculated, taking into account that

the weight of the subject was 68 kg (Figure 5).

Finally, the maximum peak power value for the first

instant was also determined (Figure 6).

Figure 3: Time-evolution of the relative acceleration.

The calculation of the proposed variables in this

study is proved possible with the data represented in

the Figures 1, 3, 4, 5 and 6. As example, the values

of the calculated variables were:

1. RT: 0.460 s;

2. TT: 2.881 s;

3. MT: 2.421 s;

4. Maximum acceleration: 13.66 m/s

;

5. Maximum velocity: 0.702 m/s;

6. Maximum Force: 929 N;

7. Maximum Peak Power: 495 W.

Figure 4: Time-evolution of the velocity.

Figure 5: Time-evolution of the force.

Figure 6: Time-evolution of the power.

4 DISCUSSION

Following the results highlighted in the previous

section, the RT of the subject used as an example

was 0.460 s. This value is higher than the RT values

referred in the literature (around 0.2 s, Wong et al.

(2015)). Two possible explanations can be stated: i)

in the present study an acoustic signal was used

instead of a visual stimulus; and ii) the 30-s CST

involves to stand up from a chair, which requires the

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296

overcoming of a much higher inertia than, for

example, the one of a rapidly touch of a button.

The maximum velocity (0.702 m/s) seems a

reasonable value by comparison with the value of

0.52 ± 0.13 m/s obtained by Regterschot et al.

(2014) with elderly people in the sit-to-stand test.

Moreover, the time-evolution of the velocity (Figure

4) clearly shows a pattern that should be expected

for a stand-up and sit-down movement. Namely, it is

seen a first peak with positive velocity

corresponding to the stand-up phase, followed by a

small plateau with velocity zero, corresponding to

the moment when the subject is standing vertically,

afterwards the velocity is negative, corresponding to

the sit-down phase. The process is continued with

the repetition of the stand-up and sit-down

movement.

The maximum peak power (495 W) is also in the

range of values reported Regterschot et al. (2014)

(423.4 ± 141.1 W) with elderly people.

The measurement of the RT and other variables

using the data acquired with the mobile device was

successful, although several constraints should be

mentioned, such as the reduced memory, low power

processing and low battery capabilities, as well as

the positioning of the mobile device during the data

acquisition process. In addition to the above-

mentioned limitations, the RT may also vary with

several conditions including healthy state, age and

physical condition (Bautmans et al., 2011).

Due to the lack of studies in the literature that

use the accelerometer sensors for the measurement

of the RT, the comparison of our method with others

is not possible. However, based on the present

results of this study and the study of Regterschot et

al. (2014), the use of the accelerometer data for the

measurement of several variables during the

performance on the 30-s CST seems reliable.

5 CONCLUSIONS

The present study highlights a novel approach on the

measurement of the RT in the 30-s CST. The results

obtained through an easy use mobile application can

be extrapolated to different research areas, including

the computer science and sports science, and studied

according to the main interests of the researchers.

The results of this study must be interpreted as

preliminary, since further validation is still needed

(like using different mobile devices and comparing

the values with other measurement methodologies).

Nevertheless, the results presented here are quite

promising and constitute an advance on the

measurement of neuromuscular variables.

In conclusion, this study is a start of a project

related to the cognitive function of elderly people,

consisting the evaluation of the 30-s CST with a

simple mobile device. However, for future work, our

method should be validated with more elderly

people.

It is also our intention to integrate this test

protocol on a scientific study, whose principal aim

will consist in the analysis of the influence of a high-

speed resistance training program on the RT and the

velocity of the movement of institutionalized elderly

people with and without cognitive disorders.

ACKNOWLEDGEMENTS

This work was supported by FCT project

UID/EEA/50008/2013 (Este trabalho foi suportado

pelo projecto FCT UID/EEA/50008/2013).

The authors would also like to acknowledge the

contribution of the COST Action IC1303 –

AAPELE – Architectures, Algorithms and Protocols

for Enhanced Living Environments.

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