Cardiovascular diseases are the leading cause of mortality, accounting for approximately 31% of all deaths worldwide [1]. The leading contributors to cardiovascular death are ischemic heart disease, ischemic stroke, hemorrhagic stroke, hypertensive heart disease (which ultimately results in heart failure), cardiomyopathy, rheumatic heart disease, and atrial fibrillation (AF) [2]. To perform cardiovascular assessments, physicians require diagnostic tools such as the electrocardiogram (ECG) [3].

The ECG records the electrical signals generated by the heart’s electrical activity; the electrical currents arise owing to potential differences that spread to the surface of the body when cardiac impulses pass through the heart [4]. The traditional 12-lead ECG is recorded via electrodes placed on the limbs and chest wall [3]. The ECG is a tool used in the everyday practice of clinical medicine, with >300 million ECGs obtained annually [5].

The 12-lead ECG is the clinical gold standard and is reminiscent of the original recordings by Einthoven, which refers to the placement of 3 limb electrodes, from which 2 leads are measured, and other 4 leads are calculated, allowing 6 limb leads and creating a view of the heart in the vertical plane [6]. In addition, the 6 precordial leads (V1-V6) provide a view of the horizontal plane of the heart, using the Wilson central terminal as a reference [3]. Technological advances such as the miniaturization of electronic components, innovations in sensor technologies, and progress in mobile and communication technology have allowed innovations in mobile health devices. New technologies allow general practitioners or ambulance staff to record ECGs as routine in chest pain, whereas patients can perform self-monitoring at home. Thus, the ECG is moving from the clinical to the domestic environment [7].

Previous review studies on mobile ECG devices have focused primarily on wearable sensors that can be used in and outside of the clinic, the technological taxonomy of ECG devices, an analysis of single- and 3-lead devices, adhesive ECG patch devices, and devices focused only on diagnosing rhythm disorders and conduction system diseases; the studies’ secondary focus has been on the future of ECG technologies, including the necessary steps for integration in clinical infrastructures [7-13]. The published reviews have shown that a majority of mobile ECG devices are focused on screening for AF or other rhythm disorders [7,8,11,13]. The reviews partly cover the potential applications of mobile ECG devices. There is a gap in how the available devices in the market can be selected for use based on device characteristics, purpose, and clinical evidence.

This review aimed to provide an overview of the mobile ECG devices that are available in the market, including the technology used, their intended clinical use, and the published clinical evidence used for validation. In this review, we defined the gaps and pitfalls in commercially available and discontinued devices to provide the reader with a comprehensive overview of the current landscape of mobile ECG devices as well as their clinical purposes, clinical outcomes, and benefits. In addition, we addressed the disadvantages per type of device to highlight the most promising devices or technology used and the areas where there is room for improvement.

First, we performed a PubMed database search for ECG devices. We searched for articles published between September 6, 2012, and September 6, 2022. Article titles, keywords, and abstracts were searched using the following search terms: “Wearable Electronic Devices” (medical subject headings [MeSH] term) AND (“Electrocardiography” [MeSH term] OR “electrocardiography, ambulatory” [MeSH term]). We only included articles published in English, and the identified devices needed to be capable of recording ECGs. We excluded devices that are only capable of recording photoplethysmography.

In addition, internet searches for mobile ECG devices using the Google search engine were performed. The search words used were “electrocardiography” combined with “mobile,” “wearable,” or “handheld.” Only ECG devices were included.

Once the mobile ECG devices were identified, we consulted their manufacturer websites to gather technical datasheets as well as user manuals and then summarized their characteristics and technical and user specifications. We also consulted the Food and Drug Administration (FDA) 510(k) Premarket Notification database and ClinicalTrials.gov to review data on devices when no data were available from the manufacturers.

After we identified the ECG devices, based on their characteristics, all devices found were classified into three types of mobile ECG devices: (1) handheld, (2) patch, and (3) wearable (as summarized in Figure 1 and Textbox 1).

For each device, we identified the intended use, recording time, and number of electrodes (instead of leads because the number of leads was not specified for some devices; it should be noted that for 3-electrode devices, 6 leads could be obtained from the calculation of the limb leads). We also detailed whether the device is stand-alone.

We registered the user characteristics (user environment, multiple areas of measurement, and setup difficulty), as well as technical characteristics (sampling rate, sampling resolution, and signal bandwidth) and compliance characteristics for use, such as the level of protection of the device against the ingress of hazardous parts and water (the ingress protection [IP] rating).

Finally, we searched for available clinical information by performing a search per device with the aim to identify the available clinical evidence regarding its capabilities. We identified the type of studies performed per device, whether the device had been validated for detection of certain heart conditions, and whether these studies had compared the device against 12-lead ECG devices or other mobile ECG devices.

We also analyzed the feasibility of these devices for home use while guaranteeing the safety of patients. We looked at home use compliance as well as analyzed the available clinical evidence for detection of heart disorders.

With the PubMed search, we identified 434 articles (Figure 2), of which we excluded 317 (73%) owing to publication date as well as not being written in English and after an examination of titles and abstracts, leaving 117 (27%) for analysis. Of these 117 publications, 73 (62.4%) were excluded because they referred to prototype devices (n=35, 48%), non-ECG devices (n=17, 23%), and design and validation of artificial intelligence algorithms (n=17, 23%) or were opinion articles (n=4, 5%). From the remaining articles (44/117, 37.6%), we identified 48 ECG devices, of which 22 (46%) were patch-based devices, 8 (17%) were handheld devices, and 18 (38%) were wearables. Subsequently, from the internet search, another 33 devices were identified: 16 (49%) were patch-based devices, 11 (33%) were handheld devices, and 6 (18%) were wearables. In total, 82 devices were identified for this review (Figure 2). For 58 (70%) of these 82 devices, we were able to find characteristics from manufacturer websites. We summarized and grouped the devices into continuous recording devices and intermittent recording devices (Figure 3).

For 3% (2/58) of the devices, the intended use information was not available from the manufacturer (Tables 1 and 2). Of the 58 devices, 21 (36%) do not state intended use regarding the detection of rhythm disorders; they are intended to be used for measuring and recording ECGs in general. However, more than half (31/58, 53%) of the devices are intended to be used when there is suspicion of arrhythmias (25/58, 43%), more specifically AF (6/58, 10%).

Adhesive patch devices are intended to be placed either at the left side (11/28, 39%) or center of the chest (17/28, 60%). Table 2 shows that these devices require setup for positioning the devices on patients, with the steps including skin preparation (shaving and removal of nonconductive skin layer via skin abrasion) as well as templates for the correct device placement, and for performing successful patient recordings. These steps are performed once because these devices are used on a longer-term basis (from >1 day up to >30 days). There are 2 types of patch devices: those in which the whole system, including 2 or 3 electrodes, is embedded in the patch and those that use disposable single electrodes attached through a cable. In the latter case, the devices aim to provide recordings that resemble 12-lead clinical ECG recordings. Patch devices are usually managed by health care centers, and analyses are performed by the manufacturer, specialized companies, or at health care centers.

The wearables category has shown to be more versatile because some of the devices (7/14, 50%) in this category are intended for intermittent use, whereas others (7/14, 50%) are intended for continuous recording. Devices in the former category are often used as daily accessories, such as the Apple Watch (Apple Inc), Amazfit Band (Zepp Health Corporation), and CART-I smart ring (Sky Labs Inc). As for the wearable devices that offer continuous recording, they can be used as garments such as T-shirts. These devices have embedded textile electrodes and can perform recordings lasting 24 hours. Although these devices offer prolonged recordings compared with the accessory wearables, only 2 (29%) of the 7 devices allow simultaneous recording and analysis.

Handheld devices are designed for patients, both for clinical and home use. Of the 14 devices, 11 (79%) rely on limb (including lower limbs) recordings, whereas 3 (21%) perform chest recordings. To record ECGs using handheld devices, no extra steps are required for preparing the area of contact, and ECGs can be recorded in <1 minute.

Patch and wearable devices can be used for at least 24 hours continuously, and these devices can include the feature to detect cardiac events automatically. By contrast, handheld devices have recording durations, initiated by patients, ranging from 15 to 120 seconds. Patients are typically instructed to perform recordings at the onset of symptoms or at specified times.

Handheld devices record ECGs via dry electrodes. These metal electrodes are manufactured from stainless steel, copper, silver or silver chloride (Ag or AgCl), or other unspecified materials. By contrast, patch devices use disposable electrodes, either commercially available or as part of the product.

Of the 58 devices with available manufacturer information, 43 (74%) are intended to be used at home. Of these 43 devices, only 21 (49%) disclosed their IP rating. Of these 21 devices, 5 (24%) have been tested for IP22 (protected from touch by fingers and objects >12 mm and protected from water spray <15° from the vertical) and 10 (48%) for higher IP, whereas 6 (29%) devices have been tested only for water IP (Tables 3 and 4).

Through the individual searches with regard to all 58 devices for which we were able to find characteristics from manufacturer websites, we found articles (n=36) that covered 22 (38%) of the devices, demonstrating their capabilities to record cardiac disorders. Of these 22 devices, 8 (36%) are handheld devices, 8 (36%) are patch devices, and 6 (28%) are wearables (Tables 5 and 6).

Of the 36 articles, 24 (66%) evaluated the devices’ capabilities to diagnose rhythm disorders [15-17,21,24,25,29-35,​37-43,49-56], whereas 7 (20%) reported on capabilities to detect rhythm disorders and other heart conditions, such as cardiomyopathy, conduction disorders, and cardiac ischemia [18,22,23,28,36,45,57]. Finally, for 3 (14%) of the 22 devices, the evidence found was regarding the evaluation of the quality of the signals recorded by them [14,19,20].

In 23 (63%) of the 36 articles, the feasibility to detect AF was studied. Studies on the Istel HR-2000 (Diagnosis SA), AliveCor heart monitor (AliveCor Inc), MyDiagnostick (MyDiagnostick Medical BV), Apple Watch (Apple Inc), Amazfit (Zepp Health Corporation), and Move ECG (Withings France SA) have reported sensitivities of <94% (range 54.5%-94%) for the detection of AF [21,28,29,31,34,43]. The Apple Watch, KardiaMobile (AliveCor), Bittium Faros 180 (Bittium), and Move ECG studies reported specificities of <90% (range 81%-86%) for AF detection [15,33,43]. For other rhythm disorders, the studies reported specificities of >85% (range 85.9%-99,6%), whereas the sensitivities ranged from 25% to 96% [18,22,45]. For cardiac ischemia detection, the Apple Watch and Beurer ME 80 (Beurer GmbH) were evaluated, and the studies reported specificities of >90% (range 93%-100%) and sensitivities of <65% (range 7%-64%); these studies included 40 and 13 participants, respectively [23,45].

The aim of this review was to provide an overview of the mobile ECG devices available in the market, including the technology used, their clinical application, and the published clinical evidence. In this review, we have identified 58 mobile ECG devices with available manufacturer information and observed that the main intended use of these devices is the detection of rhythm disorders, more specifically AF. We analyzed the relation of the technical characteristics and how these design decisions influence the capabilities of the devices to record cardiac disorders. In terms of clinical evidence, upon reviewing 2 FDA databases, we noted that most of the devices (33/58, 57%) did not require clinical validation because they have been found to be equivalent to other ECG devices in the market or to their previous versions. The published studies we found focused on the evaluation of the devices for the detection of rhythm disorders, more specifically AF.

To detect rhythm disorders, especially AF, one may only need to be able to capture basic heart rhythms. However, according to the European Society of Cardiology guidelines for the diagnosis of AF, an irregular R-R interval, absence of distinct repeating P waves, and irregular atrial activations indicate AF [58]. For home monitoring devices, it is not completely clear whether the detection of AF is solely based on the detection of irregular R-R intervals or whether they include P-wave detection as well.

For the diagnosis of AF, a 12-lead ECG is recorded only if the physician suspects AF, and the diagnosis will be provided if the ECG records an AF episode [59]. With our analysis, it is also possible to note that continuous monitoring devices show better performance in terms of sensitivity and specificity than intermittent monitoring devices. By using continuous recording systems, the chances of recording AF events are high, but it is necessary to consider that the amounts of data generated while continuous recordings could make it cumbersome to see when the AF events have been detected, as recordings are performed over periods higher than 24 hours.

For wearable devices with continuous recording systems, 16% of the recordings have been considered inconclusive by cardiologists, according to third-party comparisons [60]. It has also been reported that owing to signal processing and algorithm settings, devices such as the Apple Watch are limited in terms of diagnosing and misdiagnosing AF in comparison with medical grade devices [61]. This brings into question the value of using wearable devices with continuous recording systems for early detection of AF because these devices add more challenges to already stressed health care systems and clinical workflows [12].

Considering the clinical importance of the detection of AF as well as cardiac ischemia, the difference in the number of devices that can detect either condition is striking. The overwhelming number of devices is aimed at detecting AF, whereas no devices are intended for the detection of ischemia, and only 2 (9%) of the 22 devices have published studies for the detection of ST-segment elevation. From a technical point of view, many of the devices may not be completely limited in their capability to detect ischemia.

To detect other cardiac disorders such as ischemia, one also needs to be able to capture morphological details of the ECG. For either case, there are some technical challenges that require further discussion and are discussed in the following paragraphs.

A low number of electrodes and limited measurement area impose restrictions on the detection of all heart diseases [45,62,63]. Caillol et al [45] have shown how single-lead devices such as the Apple Watch could miss ST-segment elevation caused by ischemia in specific parts of the heart. The authors were able to demonstrate that ST-segment elevations and depressions were visible for lateral and inferior infarction, but when they attempted to record an anterior infarction, no ST-segment elevations or depressions were visible on the recordings [45]. Samol et al [64] demonstrated that performing ECG recordings with the Apple Watch (placed on the chest) allowed 6 precordial channels to be recorded in a serial manner [64]. A study using the AliveCor heart monitor showed that with only 2 electrodes, the device is capable of recording ST-segment elevations, once again by performing serial recordings [65,66]. The other device studied for ischemia detection (Beurer ME 80) also requires serial measurements. Considering the acute nature of the condition, we do not see any feasible application of this method of measuring ECGs for ischemia detection.

There is a need for ECG devices intended to detect ischemic diseases, but, as our search has shown, there are no devices intended for this purpose available in the market. There is evidence showing that methods for measurements and technologies are moving toward the detection of ischemic diseases; for example, the RELF method (in which the RELF leads record the voltage differences from the right shoulder [R] to an exploratory electrode [E], to the left shoulder [L], and to the left iliac crest [F]) has been developed using a 3-lead detection system, and when this device was tested for the detection of acute coronary artery occlusion, it showed a specificity of 96% during daily life recordings, and when ST-segment elevation myocardial infarction (STEMI) criteria on a 12-lead ECG device were observed during the interventions, the RELF method had a sensitivity of 100% [67,68].

For heart diseases other than rhythm disorders, single-lead devices allow preliminary recordings to be made, but to obtain a deeper understanding and to allow physicians to provide a diagnosis, more information should be recorded. However, one can imagine that performing studies on conditions such as myocardial infarction in acute settings, is more complex. Furthermore, the approval of a device aiming to detect a high-risk cardiac disorder would require compliance with more stringent requirements; for example, upon the detection of heart disorders such as acute coronary syndrome, it is necessary to provide rapid attention and therapy for patients. If such disorders are undetected, the life and quality of life of patients will be highly affected.

Other characteristics such as signal processing and acquisition may affect the capabilities of the device to detect various cardiac disorders. Applying filters to the captured ECG affects the waveform, which could lead to misinterpretation and misdiagnosis. Signal processing is a design characteristic that has been specified in the International Electrotechnical Commission (IEC) standard [69]. For the detection and interpretation of ischemic diseases, devices need to be able to record changes in the ST segment. The suggested update on the current standard for ECG devices specifies that devices that contain a filter with a high-pass cutoff frequency of 0.67 Hz can detect ST-segment deviations as long as filters are not modifying the phase of the ECG signal [70]. Bailey et al [71] have performed measurements to demonstrate that zero-phase filters indeed do not modify the phase of the ECG recordings. For 45% (26/58) of the devices that specify signal bandwidth, the lower limit ranges from 0.03 to 1 Hz, whereas the upper limit ranges from 25 to 1000 Hz. According to the suggested update of the standard, 17 (65%) of the 26 devices would be suitable for ischemia detection. In addition, the applied filter (zero phase or not) will influence the ability to detect ischemia; however, this is not specified for any of the devices.

Regarding signal acquisition, one of the influencing factors is the sampling frequency, which refers to the time interval of the discrete digital points transformed from the cardiac biopotentials [72]. In general, mobile ECG devices have a sample frequency of at least 250 samples per second. The applicable standard for home use does not specify the required sample frequencies [73]. The general standard for ECG devices used in the clinical environment recommends sample frequencies of at least 500 samples per second (there is no specification for devices used at home) [69,74]. According to Kligfield et al [72], most of the diagnostic information in the ECG is contained below 100 Hz in adults. We noted that all devices analyzed are capable of recording cardiac biopotentials at adequate sample rates.

Besides sampling frequency, signal resolution influences the quality of the ECG. The signal resolution refers to how biopotential signals are expressed in digits into which the input signal can be converted, based on the number of discrete steps. When a device has a resolution of 16 bits, it means that the number of measured steps between the minimum and maximum values that can be recorded is 2¹⁶=65,536. In other words, if a device can only capture signals between −2.5 V and +2.5 V (5 V at full-scale deflection), the detail that can be recorded at a resolution of 24 bits is 0.298 µV, also referred to as the least significant bit (LSB). Thus, the combination of full-scale deflection and resolution determine how little of the heart biopotentials can be captured. In fact, the question is this: what is the maximum value of the LSB that provides enough detail on the morphology of the ECG signals (the standard defines an LSB of ≤1 µV [69])?

The relationship of sampling frequency and signal resolution is relevant for diagnosis because of the added information that these features provide to physicians; for example, regarding the relationship of fragmented QRS (fQRS) and heart disorders, fQRS can only be observed when the sample rate and resolution are sufficient to capture the detailed signals. It has been demonstrated that the use of fQRS is a key feature for detecting myocardial scars in patients [75-77].

It is observed that the prioritization of a device’s characteristics depends upon its intended use. For handheld home-use devices, usability and easy-of-use characteristics are a priority in comparison with patches, where the recording is a priority and the comfort of the patient is secondary.

We believe that the prioritization regarding users starts from design decisions, such as the selection of electrodes. Adhesive patch devices use wet electrodes, whereas handheld devices and wearables use a mix of electrodes, ranging from embedded metal dry electrodes to textile electrodes that do not require skin preparation. According to electrode comparisons and reviews, wet gel electrodes provide good signal quality for short-term recordings because the gel improves the electrode-skin contact, allowing the formation of a conductive path between skin and electrode [78,79]. However, it has also been noted that long-term use of these types of electrodes can cause skin irritation, and the signal quality decreases as the conductive gels dry out [80]. Hickey et al [81] have reported that by using devices that include multiple adhesive electrodes or patch-type devices, user compliance is diminished owing to application and wearing complexity. Dry electrodes do not require a medium for conduction because the substrate is in direct contact with the skin. This metal-skin interface has been reported to influence the quality of recorded signals owing to movement artifact and charge sensitivity [79]. When biocompatible, the use of dry electrodes prevents undesirable chemical effects and skin irritation on patients [78,82].

For home-use medical electrical devices, their enclosures should provide the user protection against access of hazardous parts inside the enclosure and against harmful effects owing to ingress of water [83]. To designate a device’s degree of protection, the IP rating is disclosed. Devices must comply with the minimum IP rating of 22, which is applicable to medical home-use and health care devices [73]. Compliance with the features specified in the standard helps to guarantee the essential device performance as well as basic device safety to users and patients. Of the 38 devices meant for home use, only 14 (37%) have disclosed their IP rating in compliance with the applicable IEC standard. For the remaining devices (24/38, 63%), the IP rating has not been registered on the available device patient information; however, this requirement might be covered by the checklist of general safety and performance requirements. Of note, the devices carry the Conformité Européenne (CE) marking and meet the requirements specified by IEC standards [73,84].

Of the 58 devices with available manufacturer information, only 18 (31%) have published feasibility and reliability studies on diagnosing heart conditions. Patch devices are used as the benchmark for comparison in clinical studies, specifically if these devices have a continuous recording function (Holter devices). As for other devices with published clinical evidence, these devices perform recordings in positions that are not similar to those of the 12-lead clinical ECG. The studies are part of the clinical evidence on the route to compliance with medical device regulations for clinical testing to show the capability of the device to achieve its intended purpose, clinical performance, and benefits [85]. Upon performing the search in the FDA 510(k) Premarket Notification database, we noted that most devices do not include clinical evidence in the submissions because they show evidence of their similarities to other devices in the market or previous versions of the device in question. However, for recently released devices, such as the Apple Watch, we were able to see detailed clinical evidence summaries. We believe that because compliance requirements for new devices have become more stringent, we can expect to see more clinical evidence for new devices. Our belief is also based on the changes made to the European Union regulations governing medical devices; as other researchers have pointed out, the new regulations focus on the need for more clinical data for all medical devices [86,87].

In 2017, the medical device directive was updated to a new version, which is more stringent and aims to improve the safety and effectiveness of medical devices. One of the main changes made to the regulations concerns the additional emphasis placed on the clinical evidence of medical devices [83] to ensure their safety and effectiveness [85]. For devices without available clinical evidence, we could argue that for them to be available in the market, an important step is the clinical evaluation. Before 2017, owing to their similarities to other products already available in the market, these devices’ clinical investigations could have been based on the clinical evidence presented by similar devices. This is specifically the case if these devices have been certified before May 2021, when the European Union Medical Device Regulation became fully applicable. Nowadays, another source of information regarding the performance and safety of medical devices as well as the risks involved in using them is the postmarket surveillance; however, these activities are normally confidential, which could be the reason for the lack of available public clinical data for these devices [88].

The studies have shown promising evidence of the capabilities of the ECG devices, but they have been tested on small populations, which is a limitation in terms of investigating their full functionality and use in broader scenarios. As has been specified in the guidance regarding sufficient clinical evidence, these types of publications could be sufficient if there are no concerns regarding the safety of the patient and performance of the device [88].

For handheld devices, another observation concerned the design of the studies owing to the use characteristics of these devices. In the study by Magnusson et al [89], the recordings were limited and scheduled at certain times of the day, limiting the comparison with patch devices, which were used on a continuous basis, whereas in another study, the approach was based on patient management, with patients instructed to perform recordings when symptoms were present, which, as Doliwa et al [90] have shown, is an improvement with regard to detecting paroxysmal AF in patients who have had a recent stroke. These data were confirmed by other studies with similar approaches and outcomes [41,91]. The design of clinical studies should take into account user case scenarios that approximate to the intended use of the device in daily life. By designing studies based on user scenarios, it would be possible to compare the capabilities of handheld devices with those of patch devices when their performance is evaluated for the detection of symptomatic cardiac diseases. There is a marked lack of studies for the vast majority of the devices (35/58, 60%) included in this review, with, as mentioned previously, only 38% (22/58) of the devices having been investigated in studies regarding their capabilities to detect cardiac disorders.

To the best of our ability, we tried to perform an exhaustive search to identify all available devices; however, we cannot guarantee that all were indeed identified. In terms of the analysis performed, we were not able to summarize all technical and clinical information related to the devices owing to the lack of availability of data for such devices.

As this review shows, there is a wide range of mobile ECG devices available for home use, but as mentioned, technologies are moving toward the use of other sensors. One limitation of this review is that we have not analyzed other devices containing other types of sensors used for cardiac monitoring, such as photoplethysmography or consumer electronics not intended for detection of cardiac disorders such as the Fitbit (Google LLC); however, this was a choice because we decided to include only ECG devices.

Finally, in our analysis, we decided not to include the fact that for some devices (ie, KardiaMobile and Fitbit), users are required to sign up for subscription services to obtain further diagnosis of ECGs. We decided not to analyze the availability of these types of services because they depend on location, and prices may change over time.

We believe that the inclusion of other sensors will help to improve ECG devices’ capabilities to detect disorders. As noted by Sana et al [92], certain heart conditions are difficult to detect with ECG recordings [92]. Structural heart abnormalities can potentially be diagnosed with the help of other sensors (eg, by analyzing sound, accelerometer, and gyroscope recordings), which suggests that phonocardiograms or seismocardiograms could be added to the ECG recording [92]. We noted that, of the 58 devices included in this review, a few (n=2, 3%), such as the Eko DUO (Eko Devices Inc) and Coala Heart Monitor (Coala Life AB), already include these features. We also noted that there is a trend toward acquiring more information on the heart. During the systematic search, we came across prototypes, which included microphones, accelerometers, and gyroscope sensors, that are currently in development and in early stages of testing [93-97].

In this review, we have explored the current scope of mobile ECG devices available in the market for use at home. We have summarized the usability, technical, and clinical characteristics that could allow selection of an ECG device for patients and home use. Devices available in the market are mainly intended for the detection of arrhythmias, more specifically AF, but no devices are intended for the detection of cardiac ischemic disorders. We showed that this is due to the capabilities of the devices, such as the limited measurement areas, limited number of electrodes, and recording capabilities. Clinical research concerning the devices has been primarily focused on rhythm disorders, with few studies focusing on other heart disorders, involving small test populations. Trends in the development of mobile ECG devices are inclusion of other sensors on ECG devices to increase cardiac information collected by them and a movement toward the inclusion of embedded algorithms, allowing the diagnosing of rhythm disorders.