**3. Wearable solutions for cardiac monitoring**

Heart disease, a worldwide chronic condition, is the leading cause of death in many countries. There are various parameters that capture the characteristics of cardiac activity. Among them, resting HR is one of the simplest, yet most informative, cardiovascular parameters. Heart rate variability (HRV) has been identified as a prognostic marker for cardiac abnormalities. Although the "gold standard" for assessing cardiac abnormalities remains a 12-lead Holter, a large number of innovative and versatile wearable devices, including chest strips, wrist-worn devices, earphones, and smart clothing, have emerged as alternatives, which can provide the opportunity for prolonged, continuous cardiac rhythm tracking in real-world environments. Today, several portable devices are commercially available for determining cardiac status via a single-lead ECG, either by wearing a patch for continuous rhythm tracking [5] or using a smartphone for rhythm capture whenever needed. If multiple leads are needed to increase the accuracy of arrhythmia diagnosis, there are smart shirts that allow for 3- to 12-lead ECG monitoring [2].

#### **3.2.1. ECG patch monitor**

An ECG patch monitor (EPM) attached to the skin on the chest via an adhesive carrier generally consists of electrodes, a signal-processing subsystem, and a wireless data transmission subsystem. The two most representative examples of single-lead EPM are the Zio Patch recorder [62] and NUVANT PiiX event recorder [63].

The Zio Patch can be categorized as a single-lead Holter with a memory of up to 14 days of stored rhythms. The Zio Patch has a frequency response of 0.15–34 Hz, an input impedance greater than 3 MΩ, a differential range of ± 1.65 mV, and a resolution of 10 bits. There is a button on the patch allowing the patient to mark a symptomatic episode. Once the recording period is complete, the patient mails the patch back to iRhythm Clinical Centers (iCC), where the recorded ECG data will be processed and analyzed by the Zio ECG Utilization Service (ZEUS) system with the capability of detecting up to 10 categories of rhythms. Rosenberg *et al*. [64] compared the Zio Patch with a 24-h Holter monitor in 74 consecutive patients. The mean wear time was 10.8 ± 2.8 days. Compared with the first 24 h of monitoring, there was an excellent agreement between the Zio Patch and Holter in identifying atrial fibrillation (AF) events. In another study, Turakhia *et al*. [65] evaluated the performance of the Zio Patch in 26,751 consecutive patients. The Zio Patch was well tolerated, with a mean monitoring period of 7.6 ± 3.6 days, and the median analyzable time was achieved 99% of the total wear time. The overall diagnostic yield of the Zio Patch was 62.2% for any arrhythmia and 9.7% for any symptomatic arrhythmia.

The NUVANT system consists of a 15-cm adhesive patch named the PiiX, a wireless data transmitter called zLink® and a patient trigger magnet [66]. The PiiX sensor samples the ECG signal at 200 Hz with a resolution of 10 bits. The PiiX patch that is integrated with multiple sensors cannot only continuously monitor many physiological parameters, including HR, HRV, RR, fluid status, body position, activity, and body temperature, but also automatically identify nonlethal cardiac arrhythmias [67], including bradycardia ≤40 bpm, pause ≥3 seconds, atrial fibrillation, ventricular tachycardia or ventricular fibrillation, tachycardia HR >130 bpm, a-Fib/a-Flutter (all rates), heart block, and fall-associated arrhythmia. When an arrhythmia is detected, the PiiX sends the data to zLink via Bluetooth. The zLink then transmits the data to the monitoring center or a caregiver using cellular communication. The clinical experience of the NUVANT/PiiX is currently lacking. One study with regard to patient compliance of the NUVANT system has shown no reduction in the on-patient longevity or performance of the device [66].

The ECG patch capable of recording up to three lead signals is on its way for the public's use [69]. A three-lead PEM, developed by IMEC and the Holst Center [70], integrates an ultra-low power ECG chip and a Bluetooth Low Energy (BLE) ratio, allowed to run continuously for 1 month on a 200 mAh Li-Po battery. The IMEC patch can monitor not only three channels ECG, but also the contact impedance, providing real-time information on the sensor contact quality that is important for aiding in filtering motion artifacts. The recording data are processed and analyzed locally on ECG SoC to reduce motion artifacts using adaptive filtering or principal component analysis and compute beat-to-beat HR based on discrete or continuous wavelet transforms.

PEM is considered to be a promising technology for its unobtrusive, wireless, and long-term recording capabilities. Further studies are necessary to examine the sensitivity and specificity of the recordings and long-term impact of the use of EPM in AF.

#### **3.2.2. Smartphone-based monitor**

wearable sensors (i.e., resolution, noise level). Therefore, the effectiveness of wearable inertial-

Using a smartphone for PD management seems promising in mHealth, yet there are the same issues as those in smartphone-based fall detection systems. The performance and usability of smartphone-based solutions remain limited by the relatively lower quality of embedded sensors, and the limited battery life of smartphones, as well as the need to wear the smartphone

Only very few studies provided a complete overall assessment of PD [55, 56]. Most of the existing solutions with external wearables sensors or the smartphones built-in sensors have limited focus on a particular motor symptom, and lack the important characteristic for PDmonitoring services, such as long-term recording, qualitative and quantitative assessments. Therefore, more effort should be put into providing a complete tool that comprises the most

Heart disease, a worldwide chronic condition, is the leading cause of death in many countries. There are various parameters that capture the characteristics of cardiac activity. Among them, resting HR is one of the simplest, yet most informative, cardiovascular parameters. Heart rate variability (HRV) has been identified as a prognostic marker for cardiac abnormalities. Although the "gold standard" for assessing cardiac abnormalities remains a 12-lead Holter, a large number of innovative and versatile wearable devices, including chest strips, wrist-worn devices, earphones, and smart clothing, have emerged as alternatives, which can provide the opportunity for prolonged, continuous cardiac rhythm tracking in real-world environments. Today, several portable devices are commercially available for determining cardiac status via a single-lead ECG, either by wearing a patch for continuous rhythm tracking [5] or using a smartphone for rhythm capture whenever needed. If multiple leads are needed to increase the accuracy of arrhythmia diagnosis, there are smart shirts that allow for 3- to 12-lead ECG

An ECG patch monitor (EPM) attached to the skin on the chest via an adhesive carrier generally consists of electrodes, a signal-processing subsystem, and a wireless data transmission subsystem. The two most representative examples of single-lead EPM are the Zio Patch

The Zio Patch can be categorized as a single-lead Holter with a memory of up to 14 days of stored rhythms. The Zio Patch has a frequency response of 0.15–34 Hz, an input impedance greater than 3 MΩ, a differential range of ± 1.65 mV, and a resolution of 10 bits. There is a button on the patch allowing the patient to mark a symptomatic episode. Once the recording period is complete, the patient mails the patch back to iRhythm Clinical Centers (iCC), where

based methods in mHealth regimens still has to be further examined.

common PD motor disabilities, such as tremor, bradykinesia, LID, and FoG.

**3. Wearable solutions for cardiac monitoring**

recorder [62] and NUVANT PiiX event recorder [63].

in a fixed position.

18 Mobile Health Technologies - Theories and Applications

monitoring [2].

**3.2.1. ECG patch monitor**

Recently, a flood of smartphone-based monitors has been designed for heart rhythm moni‐ toring, which falls into two broad categories, namely smartphone-only and smartphone with external sensors.

The most representative in the smartphone-only category is the camera-based apps, which measure the cardiovascular blood volume pulse (BVP) generated by repeated, rhythmic heart contractions (that can be registered by photoplethysmogram (PPG)) using the embedded camera in the smartphone. Researchers have shown that pulse rhythm and phase information regarding the BVP waveform can be deduced from the brightness change in the red (R), green (G), or blue (B) channels [68]. Several approaches to deal with the motion artifacts in the camera signals have been proposed to improve the measurement accuracy. The MIT laboratory used the blind source separation (BSS) to separate RGB color channels into independent compo‐ nents, which demonstrated its ability to extract the HR with digital, off-the-shelf webcams in normal ambient lighting in the presence of a limited range of motion artifacts [71, 72] Fang *et al*. [73] uncovered the underlying PPG signal from a single-channel recording using the dynamic embedding technique followed by ICA. This method relies only on the inherent temporal dynamic of the single-channel signal, making it suitable for all kinds of cameras. Thus, the built-in camera in smartphones could easily double as a heart rate monitor. Camerabased apps were subsequently brought into being based on these methods. Azumio's Instant Heart Rate app [74] is one of the most popular health apps on the market, which uses the smartphone's built-in camera and flash to compute HR and update the number through placing the tip of one's finger on the camera for about 10 sec. Many apps with advanced algorithms have also been launched for noncontact measurement of heart and respiration rate, such as a Vital Signs Camera app developed by Philips Innovation [75], extracting HR from the changes in color of the face and RR from the motion of the chest.

On the other hand, some external sensors, wired or wirelessly connecting with a smartphone, are used for sensing cardiac signals. These sensors transmit raw data to the smartphone for processing and analyzing based on computational algorithms embedded on smartphones. One example of these significant achievements is the most recent FDA approved AliveCor Heart Monitor platform [76], which supports both iPhone and Android platforms. It has been designed as a smartphone case with finger electrodes that snaps onto the back of a smartphone to measure the single-channel ECG and wirelessly communicate with the app on the phone. With secure storage in the cloud, the data can be retrieved confidentially by users themselves or their physician anytime, anywhere.

Documented clinical outcomes in the scientific literature with smartphone-based monitors is lacking at present. More work still needs to be done to examine the accuracy and sensitivity of the smartphone-based monitors.
