Personalized Evaluation of Life-threatening Conditions in Chronic

Kidney Disease Patients: The Concept of Wearable Technology and Case

Analysis

Ana Santos Rodrigues

1 a

, Birut

e Paliakait

1 b

, Saulius Daukantas

, Andrius Solo

senko

1 c

Andrius Petr

enas

1,2 d

and Vaidotas Marozas

1,2 e

Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania

Department of Electronics Engineering, Kaunas University of Technology, Kaunas, Lithuania

Keywords:

Wearable Device, Smartwatch, Photoplethysmography, Arrhythmia Detection, Electrolyte Fluctuations,

Biosignal Sensors, Hemodialysis.

Abstract:

The progressive aging of society results in a one-third increase in mortality rates of chronic kidney disease

(CKD) patients over the past decade. In the end stage of CKD, 40% of deaths are sudden deaths due to

cardiac arrhythmias precipitated by electrolyte imbalance. Unfortunately, there is a lack of technology for

unobtrusive long-term monitoring of life-threatening conditions, leading to limited knowledge on arrhythmia

characteristics and their relationship with complications. This paper presents a wearable technology prototype

to monitor CKD patients between subsequent dialysis procedures. The proposed technology enables at-home

monitoring of electrolyte ﬂuctuations and detection of cardiac arrhythmias, such as ventricular tachycardia and

extreme bradycardia. A patient uses a wearable wrist-worn device to record continuous photoplethysmogram

and intermittent electrocardiogram signals together with a smart device, such as a tablet or a smartphone,

to enter meals and medications that may alter electrolyte levels. The application of the proposed wearable

technology is demonstrated in a case analysis. The developed wearable technology for monitoring CKD

patients in a home environment can be valuable for identifying patients susceptible to dangerous arrhythmias

due to electrolyte imbalance.

1 INTRODUCTION

Chronic kidney disease (CKD) affects 13.4% of the

population and is especially common among older

individuals (>65 years), leading to a one-third in-

crease in mortality rates over the past decade (Wang

et al., 2016). In the end stage of CKD, 40% of all

deaths are sudden deaths due to cardiac arrhythmias,

namely, ventricular tachycardia and extreme brady-

cardia (Kalra et al., 2018; Saran et al., 2019). While

ventricular tachycardia that eventually progresses to

more advanced stages (ventricular ﬂutter, ventricu-

lar ﬁbrillation) often precedes sudden cardiac death,

recent research has shown that extreme bradycardia

leading to asystole is also a common cause in CKD

https://orcid.org/0000-0002-5011-8192

https://orcid.org/0000-0002-4831-6587

https://orcid.org/0000-0002-1518-9366

https://orcid.org/0000-0002-5700-7196

https://orcid.org/0000-0002-6879-5845

patients (Wong et al., 2015b; Yamaguchi et al., 2020).

Thus, it is crucial to detect initial life-threatening ar-

rhythmia episodes as soon as possible to avoid a fa-

tal outcome. Unfortunately, the existing devices for

long-term continuous arrhythmia monitoring are ei-

ther invasive (implanted devices) or inconvenient for

the patient (Holter monitors, ECG patches). Further-

more, it is often unclear what factors contribute most

to arrhythmia initiation in a particular CKD patient.

The end-stage CKD is often treated with thrice-

weekly hemodialysis (HD), increasing the interval

between the procedures 1.5 times during the week-

end. About 50% of life-threatening arrhythmias oc-

cur on the last day of the long interval, linked to in-

creased volume of bodily ﬂuids and electrolyte imbal-

ance (Wong et al., 2015a), with potassium being the

most suspected arrhythmogenic electrolyte (El-Sherif

and Turitto, 2011). Electrolyte imbalance is common

and often asymptomatic in CKD patients (Brunelli

et al., 2017), therefore gathering information on elec-

244

Rodrigues, A., Paliakait

e, B., Daukantas, S., Sološenko, A., Petr

enas, A. and Marozas, V.

Personalized Evaluation of Life-threatening Conditions in Chronic Kidney Disease Patients: The Concept of Wearable Technology and Case Analysis.

DOI: 10.5220/0010905700003123

In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 4: BIOSIGNALS, pages 244-250

ISBN: 978-989-758-552-4; ISSN: 2184-4305

trolyte ﬂuctuations between HD procedures is of im-

portance for restoring the normal balance before the

onset of arrhythmias. Unfortunately, the only clini-

cally accepted method for evaluating electrolyte bal-

ance is an invasive blood test, which cannot be per-

formed at home.

Noninvasive assessment of electrolyte imbalance

spawns scientiﬁc research and technological innova-

tion. Electrolyte imbalance affects cardiac electrical

function and can be reﬂected in the electrocardiogram

(ECG). Based on this property, researchers at Mayo

Clinic (USA) are developing an ECG analysis-based

algorithm for the assessment of serum potassium lev-

els (Attia et al., 2016), whereas Medtronic (USA)

has patented the method for use in implantable de-

vices (Soykan et al., 2016).

An implantable cardioverter-deﬁbrillator is the

primary treatment against sudden death due to ven-

tricular tachycardia, while a pacemaker is prescribed

for bradycardia management. However, the usage of

implantable devices for sudden death prevention is re-

stricted by various factors, mainly the signiﬁcant cost

of the invasive device itself and implantation proce-

dures, unclear criteria for selection of CKD patients

for implantation, and their predisposition to infec-

tion (Boriani et al., 2014). Since implantable de-

vices are the only technology providing convenient

long-term monitoring of arrhythmias, such restriction

vastly limits the knowledge of arrhythmia character-

istics and their relationship with complications.

The growing interest in wearable biosensors in-

spires scientists to search for more convenient means

of arrhythmia monitoring. Detection of atrial ﬁbril-

lation in a photoplethysmogram (PPG) has already

demonstrated promising results (Bonomi et al., 2018;

Solo

senko et al., 2019; Perez et al., 2019; Pereira

et al., 2020). The potential of wrist-worn devices

capable of detecting atrial ﬁbrillation will likely en-

courage the development of detectors for different ar-

rhythmia types. Nevertheless, thus far, only a few at-

tempts to detect life-threatening arrhythmias in PPG

have been published (Bonomi et al., 2017; Paliakait

et al., 2021).

This paper presents the concept of wearable

technology for a personalized evaluation of life-

threatening conditions in CKD patients undergoing

HD. Electrolyte balance is usually altered prior to

HD and normalizes after the procedure. Accord-

ingly, we hypothesize that the corresponding differ-

ences in ECG morphology parameters are related to

the patient’s electrolyte balance before and after HD.

We also hypothesize that electrolyte ﬂuctuations may

cause life-threatening arrhythmias in some patients.

The application of the proposed wearable technology

is illustrated with a case study involving a CKD pa-

tient with electrolyte ﬂuctuations and ventricular ar-

rhythmias.

2 METHODS

2.1 The Components of Wearable

Technology

Figure 1 shows a prototype of a wearable technology

for CKD patient monitoring. A patient uses a wear-

able device for recording continuous PPG and inter-

mittent ECG signals. Also, the patient can enter meals

and medications, which may alter electrolyte levels,

using a smart device (tablet or smartphone) with a

dedicated software.

The technology ensures wearing comfort since

biosignal sensors are integrated into a wrist-worn de-

vice. By using the proposed technology, electrolyte

ﬂuctuations are monitored relying on a single-lead

short-term (1-min) ECG. The use of wires is avoided

by integrating the ECG electrodes into the device –

one at the bottom, in contact with the skin, and the

other on the top. The ECG is recorded by touch-

ing the top electrode with a ﬁnger of the opposite

hand. Meanwhile, extreme bradycardia and ventric-

ular tachycardia are detected by analyzing a PPG sig-

nal, acquired using the same device. In case life-

threatening arrhythmia is detected, the patient is in-

formed by the device (e.g., by vibration) to touch the

integrated biopotential electrode. The recorded short-

term ECG can be sent to the physician for arrhythmia

type conﬁrmation.

After the recording period, e.g., interdialytic in-

terval, the patient connects the wearable device to the

smart device where the app automatically opens the

most recent GDF (general data format) ﬁle and sends

it via HTTPS to a web API hosted on the server. The

web API is implemented in the Haskell programming

language using the Servant framework. The database

(PostgreSQL) stores data about meals and medica-

tions together with timestamps and performs synchro-

nization to the signal ﬁles. After each data ﬁle is

received, the MATLAB-based processing server, sit-

uated in a high-performance computing workstation

equipped with a GPU, processes the ﬁle and creates

a report that includes electrolyte estimates in rela-

tion to detected extreme bradycardia and tachycardia

episodes. Then the report is saved in the database and

emailed to the physician responsible for the patient.

Each of the components are described in more detail

below.

Personalized Evaluation of Life-threatening Conditions in Chronic Kidney Disease Patients: The Concept of Wearable Technology and Case

Analysis

245

Patient-worn

device

Patient’s

smart device

Physician's

smart device or PC

Electrocardiogram

Photoplethysmogram

Server

Database

Signal and data

processing

PHOTO

(a) (b)

Figure 1: (a) A prototype of a wrist-worn device for arrhythmia detection and monitoring of electrolyte ﬂuctuations to-

gether with a smartphone and a tablet for entering meals and medications. Note Lithuanian interface of an application

adapted for local patients. (b) A basic system architecture of a technology for CKD patient monitoring. Icons used from

www.onlinewebfonts.com/icon, licensed by CC BY 3.0.

2.2 Monitoring of Electrolyte

Fluctuations

Electrolyte ﬂuctuations can be recognized in ECG

since anomalous electrolyte levels affect the cardiac

electrical conduction. For instance, potassium ﬂuctu-

ations usually alter the T-wave morphology, whereas

calcium precipitates changes in the ST-segment du-

ration (Surawicz, 1967). To evaluate potassium-

induced T-wave morphology changes in HD patients,

we developed a model-based parameter, θ

, that eval-

uates global changes in T-wave morphology (Ro-

drigues et al., 2020). The T-wave, composed of

two slopes—upward and downward—is parameter-

ized using a composite model comprising one Gaus-

sian and one lognormal functions to characterize each

individual slope. θ

combines two parameters: (i) the

angle θ (in °) between the gradients of upward and

downward slopes (Figure 2a-b); and (ii) the tempo-

ral displacement δ (in s) between the modes of the

lognormal and Gaussian functions (Figure 2c-d). The

principle of θ

is as follows. As potassium level rises

above the normal level, the T-wave tends to become

more peaked and decreases in duration. The angle θ

quantiﬁes variations in T-wave peakedness, whereas δ

measures changes in T-wave elongation. θ

ampliﬁes

the response of θ and δ to potassium ﬂuctuations and

is estimated as:

= − log

(θ · δ). (1)

The logarithm expands the dynamic range and en-

sures a positive correlation of θ

with potassium ﬂuc-

tuations. θ

is estimated from an averaged heartbeat

representative of a deﬁned short period. For this pa-

per, we used a sliding window of 90 s with a 20 s over-

lap to segment a single-lead ECG. The ECG signal

is preprocessed similarly to our previous study (Ro-

drigues et al., 2020).

2.3 Detection of Life-threatening

Arrhythmias

Extreme bradycardia is deﬁned as at least 5 consecu-

tive beats at a heart rate lower than 40 bpm, and ven-

tricular tachycardia is deﬁned as at least 5 consecutive

ventricular beats at a heart rate higher than 120 bpm.

Following these deﬁnitions, life-threatening arrhyth-

mias are detected in pulse rate series, obtained from

the peak-to-peak intervals where the occurrence times

of the PPG pulses are determined using a peak de-

tector similar to the one described in (Aboy et al.,

2005). To avoid false alarms, the threshold-based

life-threatening arrhythmia detector (Paliakait

e et al.,

2021) is supplemented with a signal quality index pro-

posed in (Solo

senko et al., 2019). A PPG pulse is con-

sidered to be of high quality if maximum correlation

coefﬁcient between the pulse and a template pulse ex-

ceeds 0.8. Hence, an episode of a life-threatening

arrhythmia is detected only if at least 5 consecu-

BIOSIGNALS 2022 - 15th International Conference on Bio-inspired Systems and Signal Processing

246

After HDBefore HD

1000

1.0

0.5

Normalized amplitude

1000

Normalized time

(samples)

1.0

0.5

Normalized amplitude

1000

Normalized time

(samples)

1.0

0.5

Normalized amplitude

Before HD

After HD

208

Time (ms)

Amplitude (mV)

0.28

0.14

(a)

(c)

(b)

(d)

Normalized time

(samples)

Before HD

After HD

T-wave

Composite

Gaussian

Lognormal

Figure 2: Concept of θ

calculation: (a) original T-waves

before and after HD; (b) variation of θ in amplitude normal-

ized T-waves before and after HD. Variation of δ: (c) before

and (d) after HD. Potassium decreased from 5.5 mmol/L to

3.2 mmol/L.

tive high-quality pulses satisﬁes one of the above-

described criteria for the pulse rate. In the case de-

scribed in this paper, a reference synchronously ac-

quired continuous ECG signal was used to conﬁrm

the arrhythmia episodes detected in the PPG signal.

3 CASE ANALYSIS

3.1 Patient Description

Signals were recorded at the hospital of Lithuanian

University of Health Sciences Kaunas Clinics from

a 79-year-old male patient, with a body-mass in-

dex 30.1 kg/m

, hospitalized due to arteriovenous

ﬁstula thrombosis. Chronic kidney inﬂammation

(pyelonephritis) is a suspected unconﬁrmed cause of

CKD in this patient. The study was conducted in ac-

cordance with the ethical principles of the Declara-

tion of Helsinki and approved by the Kaunas Region

Biomedical Research Ethics Committee (No. BE-2-

43). The patient gave written informed consent to

participate in the study.

3.2 Data Analysis

Figure 3 shows the variation of θ

and blood pres-

sure throughout the monitoring period. Nine extreme

bradycardia episodes lasting for 6–10 heartbeats were

detected in the continuous PPG signal; however, three

could not be veriﬁed due to the loss of reference ECG

signal. The PPG-based algorithm also produced three

false-positive arrhythmia episodes, veriﬁed by simul-

taneously acquired ECG: one of extreme bradycardia

and two of ventricular tachycardia.

Throughout the monitoring period, systolic and

diastolic blood pressures were 121.8 ± 14.3 mmHg

and 77.6 ± 10.0 mmHg during the day, and 131.3 ±

18.5 mmHg and 79.5 ± 8.6 mmHg during the night.

Curiously, blood pressure was elevated during brady-

cardia episodes, and there was no clear indication of

nocturnal dipping.

Parameter θ

increased during HD, suggesting an

unlikely increment of potassium level, which cannot

be conﬁrmed since no blood samples were acquired.

Compared to other periods, the ECG signal quality

decreased during HD, which can disturb T-wave mor-

phology, leading to estimation errors of θ

. We also

veriﬁed that the patient displayed unusual T-waves

throughout HD upon further inspection. As elec-

trolyte levels get corrected, T-waves tend to ﬂatten.

Instead, the patient exhibited peaked and symmetrical

T-waves, typical of hyperkalemia and, perhaps, with

concomitant metabolic acidosis. Prolonged ST seg-

ments are also visible throughout the recording, hint-

ing at possible hypocalcemia.

varies coincidently with the expected potas-

sium circadian variation, decreasing from 09:00 to

11:00 and from 15:00 to 21:00 and rising from 00:00

to 09:00. Although θ

decreased during the night, θ

likely reacted to altered T-wave morphology due to

body position changes.

4 DISCUSSION

The proposed technology for in-home use is beneﬁ-

cial for investigating electrolyte ﬂuctuations as pos-

sible instigators of life-threatening arrhythmias. The

technology has both scientiﬁc and clinical signiﬁ-

cance. The acquired knowledge of arrhythmia occur-

rence, progression, temporal distribution, and causal

relationship with electrolyte ﬂuctuations could be

used to predict the course of the disease, personalize

medication, and assess the risk of sudden death for

individual patients.

Despite the recently spurred scientiﬁc interest in

non-invasive monitoring of electrolyte ﬂuctuations,

most research focuses predominantly on the devel-

opment of potassium biomarkers (Rodrigues et al.,

2020; Palmieri et al., 2021; Attia et al., 2016; Corsi

et al., 2017), neglecting, thus far, calcium, bicarbon-

ate, and magnesium. While potassium is a well-

Personalized Evaluation of Life-threatening Conditions in Chronic Kidney Disease Patients: The Concept of Wearable Technology and Case

Analysis

247

PPG

only

Bradycardia

Reference

ECG lost

Cu tube

kinked

Arrhythmia

Time

Hemodialysis Sleep

Blood Pressure

(mmHg)

θ (°s)

Bradycardia

False

Tachycardia

False

Bradycardia

False

Tachycardia

Figure 3: Variation of θ

and blood pressure throughout the monitoring period. Vertical lines indicate detected arrhythmia

episodes: solid red – true bradycardia, dashed red – false bradycardia, dashed blue – false tachycardia. A solid black curve is

a moving average of θ

estimated from all 90 s segments in a single-lead continuous ECG, and dots are the estimated values

of θ

every 15 min. Upward- and downward-pointing triangles indicate systolic and diastolic blood pressure values from an

ambulatory monitor, respectively.

known arrhythmogenic agent in CKD patients, the

entire panel of blood electrolyte levels is necessary

to understand what electrolyte combinations provoke

life-threatening arrhythmias. Even from a technolog-

ical point of view, any algorithm for assessing blood

potassium level needs to consider the remaining elec-

trolytes. Concomitant electrolyte imbalance (e.g., hy-

perkalemia and metabolic acidosis) can alter the T-

wave morphology differently than isolated potassium

abnormalities (Severi et al., 2002), thus inﬂuencing

the results of any developed biomarker (Rodrigues

et al., 2020).

Albeit unconﬁrmed with blood tests, the presented

case study illustrates the necessity of monitoring all

electrolytes instead of solely potassium. In our pre-

vious study, unexpected variations of θ

were found

in patients with severe hypocalcemia and pH imbal-

ance (Rodrigues et al., 2020), which we suspect the

patient of this case study may have had due to a pro-

longed ST-segment and peaked T-waves. Hypocal-

cemia decreases cardiac contractility and is a likely

trigger of bradycardia (Loewe et al., 2019; Yam-

aguchi et al., 2020). The unanticipated variation of θ

observed in this case study challenges us to question

our knowledge regarding the arrhythmogenic poten-

tial of different electrolyte ﬂuctuations. It further sub-

stantiates the need to continue developing technolo-

gies for ambulatory assessment of electrolyte ﬂuctua-

tions that take into account various electrolytes.

The rapid development of electronics opened the

possibility to acquire a short-term ECG by employ-

ing a wrist-worn device with two integrated biopoten-

tial electrodes. Thus far, such technological principle

is used only for personal purposes, such as obtaining

an instantaneous heart rate, without analyzing ECG

morphology which is unsurprising since comprehen-

sive ECG analysis requires good signal quality and

computational resources. In principle, the ECG sig-

nal quality can be assessed in real-time with an indi-

cation for the patient to make some contact adjust-

ments. However, real-time morphology analysis is

more challenging and still demands ofﬂine process-

ing, as preferred in the presented case study. Signal

quality issues are also particularly common in PPG

acquisition. While overlooked noise and artifacts may

produce false arrhythmia alarms, especially tachycar-

dia, eliminated poor-quality segments of PPG signal

may result in missed arrhythmia episodes (Paliakait

et al., 2021). This issue should not be overlooked

when evaluating the relationship between electrolyte

ﬂuctuations and life-threatening arrhythmias.

BIOSIGNALS 2022 - 15th International Conference on Bio-inspired Systems and Signal Processing

248

5 FUTURE WORK

The proposed wearable technology could serve for

obtaining knowledge regarding causal relationships

of electrolyte ﬂuctuations with arrhythmia develop-

ment and sudden cardiac death. Algorithms for iden-

tiﬁcation of the causal direction, coupling delay, and

causal chain relations from time series could be ap-

plied (Huang et al., 2020).

Information on the occurrence of life-threatening

conditions is valuable for developing a system for per-

sonalized decision support, for instance, implemented

as a deep recurrent neural network based on long

short-term memory, such as described in (Kwon et al.,

2018). The neural network can consist of three time

series inputs involving information on signal quality,

electrolyte ﬂuctuations, and temporal distribution of

arrhythmia episodes. Temporal distribution that car-

ries important information about arrhythmia progres-

sion can be characterized using a model-based ap-

proach (Henriksson et al., 2021). The output of the

personalized decision support system may be a sud-

den cardiac death risk score.

The proposed framework for personalized deci-

sion support can potentially be adapted for other

groups with an increased risk of electrolyte ﬂuctua-

tions and life-threatening arrhythmias, e.g., those with

heart failure or receiving chemotherapy treatment.

6 CONCLUSION

An unobtrusive noninvasive technology for monitor-

ing electrolyte ﬂuctuations and detecting ventricular

tachycardia and extreme bradycardia in a home en-

vironment can be of value for identifying patients

susceptible to dangerous arrhythmias precipitated by

electrolyte imbalance.

ACKNOWLEDGMENTS

This work was supported by the European Regional

Development Fund with the Research Council of

Lithuania under the Project 01.2.2-LMT-K-718-01-

0030.

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