# A Real Time and Lossless Encoding Scheme for Patch Electrocardiogram Monitors
## 1 Introduction  
According to the World Health Organization, cardiovascular diseases (CVD) are the leading cause of death worldwide [1]. An estimated 17.7 million people died from CVD in 2015, representing 31% of all global deaths. Of these, an estimated 7.4 million and 6.7 million deaths were caused by coronary heart disease and stroke, respectively. Of the 16 million people aged under 70 years who died from non-communicable diseases in 2011, 37% of these deaths were caused by CVD, and 82% of them lived in low and middle-income countries, where people often do not have access to integrated primary health care programs for the early detection and treatment of such illnesses. The cost of CVD treatment escalates quickly with the rapidly increasing requirements for supervision and medical management, and traditional health care infrastructures are easily overwhelmed by the demands of effective late-stage treatment. However, such costs can potentially be reduced by using systems that monitor individuals in the course of their daily activities, which would thus reduce the need for inpatient care or visits to the primary physician. Early detection and prevention are critical for reducing both the direct and indirect costs of CVD, and researchers have responded to this need by focusing on improving techniques that assess cardiac function, including electrocardiogram (ECG) analysis, which helps screen for various cardiac abnormalities. Current ECG monitoring systems provide continuous, simple, risk-free, and inexpensive recordings of the heart's electrical and muscular functions [2], and advances in technology have changed the way that ECG signals are collected, stored, and analyzed to realize \"proactive health care\". This has enabled continuous health care monitoring through the use of smartphones [3; 4; 5; 6; 7], because ECG signals can be easily transmitted through common communication channels (such as phone lines or wireless channels). In addition, wireless body sensor networks (WBSNs) [8; 9] promise large-scale solutions and can be used in place of mobile phones. These solutions automatically report cardiac signals to health care providers, which make them extremely useful in ambulatory settings. To minimize power consumption and enable long-term ECG data logging, a Holter monitor is used to record patients' ECG data offline continuously for 24-72 h. However, the Holter device does not analyze data or detect a disease, and it does not provide calculated diagnosis information to the hospital, doctor, or patient in response to a critical heart condition. Nevertheless, it has emerged as the most common ECG battery-operated platform that does not have cellular or WBSN connections [10]. Advances in semiconductor technology have enabled additional ECG signal storage with even lower power consumption; these ECG signals provide information that is subsequently used by clinicians to determine the mechanisms underlying CVD, and this development is expected to ultimately lead to effective treatment. The emerging trend is to use wearable devices to record patients' ECG data [11]. However, the Holter device typically has six to 10 sensors that must be arrayed on the body, which makes it inconvenient for everyday use. Recent technological advances have thus produced single-use, wearable, monitoring devices that are capable of continuously recording ECG signals for a period of three days or more. A wearable patch ECG monitor (PEM) records ECG signals using an embedded electronic circuit that is attached to a patient's chest with invisible electrodes and lead wires. The device can be considered a wearable health care system that is based on the use of knitted integrated sensors connected to electrodes using a conductive and piezoresistive yarn [12]. PEMs are typically highly energy-efficient and provide an analog readout application-specific integrated circuit (ASIC) for signal acquisition, amplification, and analog-to-digital conversion.