Real-Time Stand-Up Evaluation Using Low-Cost Hardware

Luis Rodriguez-Cobo

, Guillermo Diaz-Sanmartin

2,3

, Jose Francisco Algorri

1,2,4

Carlos Fernandez-Viadero

4,5

, Jose-Miguel Lopez-Higuera

1,2,4

and Adolfo Cobo

1,2,4

CIBER-BBN, Instituto de Salud Carlos III, Spain

Photonics Engineering Group, Universidad de Cantabria, Spain

Department Communications Engineering, University of the Basque Country, Spain

Instituto de Investigacion Sanitaria Valdecilla (IDIVAL), Spain

Psychiatry Service, Marqu

es de Valdecilla University Hospital, Spain

Keywords:

Wireless, Load-Cell, Real-Time Monitoring, Sarcopenia, Frailty.

Abstract:

In this study, we’ve equipped an ordinary chair with budget-friendly electronics capable of tracking the tem-

poral distribution of weight changes. This electronic system is speciﬁcally crafted to analyze typical human

motions, such as sitting down and standing up. These everyday movements greatly affect different motor

skills, such as walking patterns, the likelihood of falling, and insights into sarcopenia. However, there’s no

precise way to measure the quality of these actions, lacking an absolute standard. To tackle this issue, the

developed analyzer incorporates variables like Smoothness and Percussion, aiming to enhance information

and establish an objective metric in evaluating stand-up/sit-down actions. This approach not only introduces

a more precise assessment but also provides clinicians with additional insights, making the evaluation more

objective and informed.

1 INTRODUCTION

In the past few decades, Europe has undergone a sig-

niﬁcant demographic transition, presenting unprece-

dented challenges in caring for older individuals. Cur-

rent healthcare systems, structured around the con-

ventional medical approach to single acute illnesses,

are largely unprepared to address the complex med-

ical needs of older individuals dealing with often

chronic multimorbidities, geriatric syndromes, and

polypharmacy (Nishimura et al., 2017).

While extending life remains a crucial public

health goal, the preservation of the capacity to live

independently holds even greater signiﬁcance. Dis-

abling conditions not only burden individuals but also

strain the sustainability of healthcare systems (Linde-

mann et al., 2003).

In this context, the geriatric syndrome of frailty

and potential interventions targeting this condition

have gained particular relevance (Anabitarte-Garc

ıa

et al., 2021). The term ’frailty’ in older individu-

als has garnered increasing interest, with various pro-

posed deﬁnitions and assessment tools (Pozai et al.,

2016). Despite the efforts of many researchers, a

universally agreed-upon deﬁnition and standardized

evaluation methodology are still elusive.

Sarcopenia, deﬁned as the loss of skeletal muscle

mass and strength due to aging, stands out as a major

phenomenon in the aging process and a widely dis-

cussed topic in geriatric literature (Shum et al., 2009).

Shifting the discussion towards the consequences of

sarcopenia, such as reduced functional reserve linked

to movement capacity, may facilitate the development

of a framework and theoretical organization for the

condition. This shift moves from a purely speculative

response to an answer that can be effectively trans-

lated into clinical practice. Only in this case can we

reach a consensus on what needs evaluation and how

to assess it. Such a process is essential for gaining

the endorsement of regulatory agencies, ensuring that

sarcopenia and physical frailty become clinically rec-

ognized conditions and important targets for interven-

tions (Hughes et al., 1994).

People are becoming more aware of sarcope-

nia as a consequence of aging, and it’s linked to a

higher chance of negative outcomes like falls, frac-

tures, frailty, and mortality. Various methods have

been suggested for evaluating muscle mass, strength,

and physical performance in clinical trials. Although

these tools have shown accuracy and reliability in re-

Rodriguez-Cobo, L., Diaz-Sanmartin, G., Algorri, J., Fernandez-Viadero, C., Lopez-Higuera, J. and Cobo, A.

Real-Time Stand-Up Evaluation Using Low-Cost Hardware.

DOI: 10.5220/0012359800003657

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2024) - Volume 1, pages 117-122

ISBN: 978-989-758-688-0; ISSN: 2184-4305

117

search settings, applying many of them to everyday

practice isn’t straightforward.

In the present work, a budget-friendly electron-

ics capable of tracking the temporal distribution of

weight changes has been integrated into a chair to ob-

tain relevant data from a commonly human posture:

sitting and standing up. People perform this action

several times throughout the day, and there is a rele-

vant interaction between the quality of these actions

and other motor capabilities (Nishimura et al., 2017)

such as speed and other gait parameters, fall risk (Lin-

demann et al., 2003), or even information on sarcope-

nia (Pozai et al., 2016).

The quality of sitting or standing actions is not

an absolute value, and there is currently no quali-

tative and objective measurement for this parameter.

Time is the most important variable that can be mea-

sured and compared between different samples, but it

is known that the distribution of energy around body

parts can provide an additional source of information

(Shum et al., 2009).

There are many tests that include a sit-

ting/standing task, mainly in older people or in some

types of rehabilitation, usually in relation to lower

body strength or movement (Chow et al., 2019). One

of the most popular is the Timed Up and Go test (Her-

man et al., 2011), which consists of getting up from

a chair, walking several meters, turning 180 degrees,

returning and sitting down again, and measuring the

time spent. Another similar test consists of repeating

the lifting of a chair, and there is a relationship be-

tween the two (Hughes et al., 1994).

However, the analysis of the stand-up/sit-down ac-

tions in the course of these tests still depends on the

experience of the clinical staff, and new methods for

the systematic evaluation of these actions are needed.

Therefore, based on the designed analyzer, different

variables (Smoothness and Percussion) have been de-

ﬁned to provide more information on the process and

allow these measurements to be objectiﬁed.

2 MATERIALS AND METHODS

In the search for simplicity of use, we propose to use

a routine action (getting up and sitting on a chair) as

an indirect indicator of frailty. The main idea of this

work is to analyze the temporal evolution of weight

transfer from the chair to the feet of the individual

when standing up. Likewise, during the sitting pro-

cess, the opposite transfer will be studied: from the

individual’s feet to the chair. This section describes

both the basic scheme of the proposed analyzer and

the metrics used to quantify this process.

ADC

Figure 1: General description of the proposed device.

2.1 Instrumented Chair

Starting from a standard chair of height 50 cm without

armrests to minimize the inﬂuence of the arms during

analysis, four load cells are incorporated to each chair

leg. Also, an electronic system is designed to interro-

gate these load cells with a high sampling frequency

(1kHz) and send the data wirelessly to a control com-

puter that allows synchronization with other systems.

An scheme of the proposed design is depicted below:

Figure 2: Actual images of the prototype: the four compres-

sion load cells are the only contact points with the ﬂoor.

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118

Four high precision FC23 compression load cells

from TE Connectivity company capable of measur-

ing from 0 to 226.80kg (500lbs) are located under

each chair leg. The ampliﬁed Wheatstone bridge

signal provided by each sensor is connected to a

four-channel precision Delta-Sigma ADC (analog-to-

digital converter) (ADS1219) capable of operating at

1kHz. With an effective resolution of 20 bits, it pro-

vides the load value of each of the sensors through

the I2C (Inter-Integrated Circuit) bus. The ADC is in-

terrogated by a generic microcontroller of the ESP32

family from Espressif Systems, which is a low-power

system on a chip (SoC) with Wi-Fi and dual-mode

Bluetooth capabilities. It is a dual core microcon-

troller with a clock rate up to 240 MHz which of-

fers enough computational power and connectivity to

implement signal preprocessing algorithms and send

data over wireless.

In order to minimize noise, each measure given

by the microcontroller is the average of 3 correlatives

measures. All the data collected from each leg and the

summation of them are sent via Wi-Fi to an external

application at an effective frequency of 50 Hz. TCP

(Transmission Control Protocol) protocol has been se-

lected for this communication to guarantee that the

data will arrive at the destination without errors and

in the same order in which it was transmitted.

Once the prototype device is completed, a series

of weights in the range of 10kg to 50kg are used to

calibrate the response of each load cell. The device

thus sends the aggregate weight data supported by the

chair via Wi-Fi at a refresh rate of 50hz.

Time

Weight

Figure 3: Graphic representation of the Smoothness curves.

Pronounced peaks resulting from difﬁculties in standing

(top). Smooth line without peaks indicating correct stand-

ing (bottom).

Time

Weight

Figure 4: Graphic representation of the Percussion curves.

Pronounced peak resulting from difﬁculties in sitting (top).

Smooth curve without peaks indicating correct sitting (bot-

tom).

2.2 Passive Parameters

As mentioned in the introduction, one of the aims is

to create parameters that are capable of objectively

quantifying the information provided by the Smart

Chair, and since in the chair there are mainly two ac-

tions, sitting and standing, we propose a new param-

eter for each action, the Smoothness and the Percus-

sion, respectively.

2.2.1 Smoothness (S)

Smoothness, S, can be deﬁned as a value that pro-

vide information about the body dynamics when it is

standing, and it is related to the number of attempts

a person makes until they can get up. Each attempt

involves an oscillation in the weight curve, and the

magnitude of this oscillation together with the num-

ber of them generates a value of S. Mathematically,

Smoothness can be deﬁned as:

S =

(

1 n = 0

1 − K ·C n > 0

(1)

K being a variable that depends on the weight vari-

ations in the period prior to incorporation, with the

form:

K = 1 −

∑

i=1





(2)

where n is the number of minimums registered, x

is the value of each one of them, and w is the weight

registered by the scale when the person is sitting at

rest. Finally, C is a value that penalizes the number of

Real-Time Stand-Up Evaluation Using Low-Cost Hardware

119

minimums in the curve, so that if there are many im-

portant ﬂuctuations, the Smoothness is less, and has

the form:

C =











0 n = 1

1 +



K − 1



1 < n ≤ 10

n > 10

(3)

This means that if the Smoothness is high, stand-

ing is more correct, and if it is low, person has more

difﬁcult to perform it. In addition, if n > 0, S is

highly penalized, and if someone needs more than

ten attempts, Smoothness is zero. On other hand,

the reason a larger minimum is more penalized than

a smaller one is because more energy has been ex-

pended. Therefore, when more energy is expended in

a failed attempt, the penalty is greater.

2.2.2 Percussion (P)

The other theoretical parameter that we propose is

the Percussion, P. In physics percussion refers to the

great force (F

∼

inf) exerted on an object at a given

instant (∆t ≈ 0). We use this term to refer to the force

exerted by the human body when the person sits in

the chair in relation to its force while sitting at rest.

In other words, it is a value that relates the relative

weight increase between the weight at rest and the

weight at the time the person sits down, and is de-

scribed by:

P = 1 −

(4)

where w

is the weight measures by the chair when

the person is sitting at rest, and w

is the weight mea-

sures by the chair at the instant the person is down.

Accordingly, Percussion is strongly related with

the low limbs force. If a healthy person performs

this test, the value of P will be low, since they will

gradually sit in the chair without sudden hits. How-

ever, if the person is not able to maintain his or her

own weight in some point of the action, a peak in the

weight curve will be generate by the hit and the Per-

cussion will be higher. Percussion values values range

from zero to a limit of one. The greater the weight in-

crease with respect to the rest, the greater the value

of the Percussion, whose limit is one for an inﬁnite

increase

2.3 Experimental Setup and Results

The proposed device has been installed into Pho-

tonics Engineering Group facilities at University of

Cantabria. Leaving a free space of several meters in

front of the chair, the chair is placed together with

some marks on the ﬂoor in order to perform a refer-

ence test for the analysis of frailty: Timed up and Go

(TUG) (Herman et al., 2011). The TUG consists of

measuring the time it takes a person to get up from

a chair, walk a few meters (3-4m) at his or her usual

pace, turn around, return to the chair and sit down.

In order to establish the usability of the device, a

study was carried out with volunteers without mobil-

ity problems to establish baseline values for the met-

rics developed and compare them with the reference

time of the Timed Up and Go test. In addition, dif-

ferent speciﬁc tests have been carried out to test the

detection extremes of the proposed variables.

Figure 5: Simulation of weight change during the stand-up

of a person with reduced mobility. The measured Smooth-

ness for this change is S = 0.11.

2.3.1 Smoothness and Percussion Evaluation

The device has been used to evaluate the get-up

and sit-up of 15 healthy volunteers (13 men and 2

women), within the TUG test whose characteristics

have been summarized in Table 1. As expected, all the

tests performed by the volunteers offer baseline pa-

rameters in accordance with the variable deﬁnitions.

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120

Table 1: Characteristics of 15 volunteers. *Body Mass Index. Percussion and Smoothness are compared to the total time

spent during the Timed Up and Go test.

Age (years) Weight (Kg) Height (m) BMI (Kg/m2) P S TUG time (s)

28 66 1.75 21.55 0.23 1 8.2

31 83 1.82 25.05 0.11 1 9.8

38 74 1.6 28.9 0.25 1 11.8

32 60 1.73 20.04 0.12 1 9.33

44 93 1.78 29.35 0.06 1 9.27

50 64 1.7 22.14 0.31 1 7.03

48 106 1.82 32 0.1 1 9

24 74 1.83 22.09 0.16 1 8.8

25 77 1.78 24.3 0.04 1 9.3

37 95 1.84 28.06 0.09 1 8.03

30 75 1.68 26.57 0.26 1 6.47

34 100 1.84 29.53 0.2 1 7.83

28 72 1.65 26.44 0.13 1 7.73

26 81 1.72 27.37 0.15 1 9.77

69 90 1.69 31.51 0.08 1 10.07

Figure 6: Simulation of weight change during the sit-down

of a person with reduced mobility. The measured Percus-

sion for this change is S = 0.62.

The Percussion variable, associated with the impact

of sitting back in the chair, offers a high granularity

allowing a complementary classiﬁcation to the total

time spent in the Timed Up and Go test. Smoothness,

on the other hand, offers a warning when the person’s

mobility is quite impaired and needs several attempts

to get up from the chair.

Since Smoothness is a parameter that will always

provide 1 when the monitored persons have a degree

of functional mobility, speciﬁc laboratory tests have

been performed simulating scenarios in which a per-

son needs several attempts (3) to ﬁnally be able to get

up from the chair. The results of these tests can be

seen in Figure 5.

Laboratory tests have also simulated situations in

which the patient does not correctly control the ac-

tion of sitting back in the chair. A typical situation

for people with mobility problems is that they drop

their body when sitting down, causing a sudden im-

pact against the chair. The Percussion variable reﬂects

this situation by offering a value higher than the refer-

ence values obtained in the initial tests. This situation

is exhibited in ﬁgure 6.

3 SUMMARY AND

CONCLUSIONS

This work presents a new non-invasive device and

method that helps in the determination of the degree

of physical functionality of patients. By using low-

cost electronics, it is possible to obtain reliable and

repetitive information of a widely repeated process

in the daily routine of people: sitting down and get-

ting up from a chair. The proposed device is based

on instrumenting each of the four legs of a common

Real-Time Stand-Up Evaluation Using Low-Cost Hardware

121

chair without armrests with load cells. Using a 32-bit

microcontroller with WiFi communication capability,

the different load cells are interrogated by means of

an analog-to-digital converter and the data is sent to

a control computer. This platform allows us to ob-

tain in real time the weight supported by the chair,

being able to obtain different weight transfer proﬁles

from the chair to the feet or vice versa. Using this

tool as a basis, two new variables have been deﬁned,

Smoothness and Percussion, which try to provide ob-

jective values complementary to those currently used

in the clinic. Both the device and the deﬁned vari-

ables have been tested in laboratory conditions to ob-

tain reference values for healthy individuals without

mobility problems. Also, trying to ﬁnd representative

values for each of the variables, speciﬁc tests have

been performed simulating that the patient does not

offer a good motor function. Based on all these tests,

it is concluded that both the device and the deﬁned

variables offer greater granularity in the quantiﬁcation

of standard tests used in clinical settings such as the

Timed-Up-and-Go timing test. In summary, this work

encompasses the design and testing of a easily deploy-

able device in clinical environments. Both the device

and the addressed variables are easy to understand,

allowing for easy integration into the clinical mon-

itoring of patients with various pathologies, even in

tests currently employed such as the Timed-Up-and-

Go. Such potential clinical integration will enhance

the objective information available for assessments of

complex processes, such as motor function, enabling

better monitoring and early detection of critical situa-

tions.

ACKNOWLEDGEMENTS

This work has been supported by FEDER funds of

European Comission. Also, J.F.A. received funding

from MCIN of Spain under Juan de la Cierva grants.

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