# Inertial Sensors-Based Assessment of Human Breathing Pattern: A Systematic Literature Review
## 1 Introduction  
Breathing, an innate and vital biological process, plays a fundamental role in shaping human interactions and activities of daily living. Recognizing and analyzing variations in its pattern has profound clinical significance, offering information about potential respiratory dysfunctions [1; 2; 3; 4] and its impact on postural stability [5; 6]. Such disorders can lead to musculoskeletal problems, chronic pain, and fatigue, ultimately affecting individuals' interactions with their surroundings, leading to disability [7; 8; 9; 10; 11]. In a physiotherapy clinical evaluation setting, the breathing pattern (BP) is typically assessed through a direct observation of chest and abdominal wall motion to gather information about rhythm (respiratory frequency/amplitude ratio), location, and symmetry of motion (right vs. left, chest vs. abdominal), as well as the inspiratory/expiratory (I:E) ratio [5]. However, this evaluation method requires considerable observer expertise and may induce the \"Hawthorme Effect\" in patients, altering their BP due to the awareness of being observed [12; 13; 14]. To complement direct observation, several alternative approaches can be found in the literature. Spirometry, for instance, provides valuable insights into lung volumes, lung capacities, and breathing rhythm but has limitations in assessing chest wall motion and regional contributions [15; 16]. Optoelectronic plethysmography, considered the gold standard for biomechanical analysis, offers an accurate measurement of chest wall movements and estimation of lung volumes, but its complexity, time-consuming setups, and the requirement for a large number of infrared camera devices makes it unsuitable for routine clinical use due to its cost and technical demands [17; 18]. CT scans and X-rays offer high precision but are costly and not suitable for real-time assessment [19; 20; 21]. Depth camera devices allow for the observation of chest displacement, but like optoelectronic devices, relevant data collection depends on the subjects being within the camera's view angle, and data acquisition quality is influenced by ambient lighting conditions [22; 23; 24; 25]. Radar devices are also reported as good non-intrusive alternatives for assessing BP, but the technologies available for medical devices have limitations. They require high power energy to transmit a short pulse period signal [26] and face issues with measuring tiny positional changes and signal interference from other moving objects around the subjects [27]. Additionally, their signal acquisition depends on the distance between the subjects and the radar, limiting their use to specific locations. They also cannot differentiate between right vs. left chest wall motion asymmetries [26; 28; 29; 30; 31]. Similarly, Wi-Fi-based devices offer convenient assessment of breathing rhythm but lack the ability to differentiate between right vs. left chest motion, upper vs. lower chest, and chest vs. abdominal motion [32; 33; 34]. Inductive respiratory plethysmography provides a non-intrusive option for assessing BP but also lacks the ability to differentiate chest wall right vs. left motion asymmetries [35]. Measuring tape, despite its reported high reliability in chest mobility measurements, shows wide variability in measurements between observers (2.03-4.29 cm) [36; 37]. Palaption evaluates the mobility of the chest and abdomen by using bare hands to feel and quantify the amount of movement in the area under assessment, which can significantly induce changes in the patient's actual BP [38; 39]. Despite the advantages of all the alternatives mentioned above, their limitations make them less suitable for a clinical physiotherapy setting as they lack the ability to simultaneously evaluate all mentioned variables with optimal cost-effectiveness and time efficiency. Moreover, they are not suitable for the real-time monitoring of BP in patients' daily living activities and social interaction contexts without signal acquisition constraints.