## 1 Introduction  
Respiratory disorders are prevalent worldwide, with an estimated 454.6 million cases of chronic respiratory illnesses, which have seen a 39.8% increase during the last 30 years [1]. Climate change and increasing air pollution are negatively affecting respiratory health globally, and there is an increasing death toll due to respiratory illnesses [2]. Non-communicable chronic respiratory diseases, i.e., asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis, and mesothelioma, have caused the deaths of an estimated 4.1 million people worldwide in recent years [3, 4], while infectious lung diseases have killed about 2.5 million people in the same time period [5]. Acute respiratory infections often need hospitalization of the patient along with administration of antibiotics and medical care.  
Chronic respiratory conditions affect the life quality of patients in the long term, as they often require medication and monitoring of prognoses. Respiratory function assessment is crucial for the early identification of potential respiratory disorders, playing a critical role in guiding interventions and management strategies.  
Over recent decades, there has been a significant body of research dedicated to enhancing respiratory monitoring systems and refining pulmonary function assessment through advanced sensor technologies. Pulmonary function tests (PFTs) are instrumental in examining key parameters in individuals with respiratory conditions, aiding in treatment during both the diagnostic and recovery phases. Among these tests, spirometry stands out as the conventional method for the measurement of respiratory functioning, which is typically conducted using a pneumotachometer (PnT). This approach requires the individual to use a mouthpiece for the direct measurement of changes in internal ventilation. Another time-intensive PFT method, full-body plethysmography, demands significant patient cooperation [6; 7].  
Substantial resources have been mobilized in recent years, particularly due to the SARS-CoV-2 pandemic, to enhance medical diagnostics, develop wearable sensors, and create technologies for identifying various pulmonary diseases. The adoption of wearable sensor technology for health monitoring has experienced a significant uptick, especially within the domain of respiratory health. Numerous studies have explored the potential of breath monitoring devices and the application of sensors in evaluating pulmonary functions [8]. These pulmonary function tests (PFTs) are indispensable in assessing the respiratory health status of individuals with confirmed or potential respiratory conditions, providing crucial insights into their health status.  
Respiratory Inductive Plethysmography (RIP) is a non-invasive measure for monitoring key respiratory parameters, i.e., respiratory rates and volumes, which has been thoroughly studied as an alternative to spirometry due to its convenience of use and wide range of applications. RIP can be used in both stationary and ambulatory subjects and is generally suitable for continuous long-term monitoring, which offers an advantage over traditional spirometry in some specific cases [9; 10; 11]. Moreover, analysis of breathing patterns from RIP data can be used in diagnostic procedures in some illnesses associated with respiratory functioning [12; 13]. With the advancement in computation and signal processing techniques, RIP has huge potential to be used as an alternative alongside some other established methods in clinical practices. Numerous studies have examined the validity of RIP and implemented this technique in their research methodologies. This review work carefully examines the current literature to synthesize data and provide a conclusive statement on the feasibility of RIP in healthcare applications.