Depth-Based Measurement of Respiratory Volumes: A Review

Abstract

Depth-based plethysmography (DPG) for the measurement of respiratory parameters is a mobile and cost-effective alternative to spirometry and body plethysmography. In addition, natural breathing can be measured without a mouthpiece, and breathing mechanics can be visualized. This paper aims at showing further improvements for DPG by analyzing recent developments regarding the individual components of a DPG measurement. Starting from the advantages and application scenarios, measurement scenarios and recording devices, selection algorithms and location of a region of interest (ROI) on the upper body, signal processing steps, models for error minimization with a reference measurement device, and final evaluation procedures are presented and discussed. It is shown that ROI selection has an impact on signal quality. Adaptive methods and dynamic referencing of body points to select the ROI can allow more accurate placement and thus lead to better signal quality. Multiple different ROIs can be used to assess breathing mechanics and distinguish patient groups. Signal acquisition can be performed quickly using arithmetic calculations and is not inferior to complex 3D reconstruction algorithms. It is shown that linear models provide a good approximation of the signal. However, further dependencies, such as personal characteristics, may lead to non-linear models in the future. Finally, it is pointed out to focus developments with respect to single-camera systems and to focus on independence from an individual calibration in the evaluation.

Keywords: contactless measurement; kinect; respiratory measurement; structured light; tidal volume; time-of-flight; vital capacity.

Figure 1

Schematic representation of the change in volumes over time.

Figure 2

Marker-based and direct methods for measuring depth: (a) Use of markers and multiple cameras for depth determination by opto-electronic plethysmography; (b) Direct measurement methods to measure the depth values. Use of two offset cameras for active stereoscopy. Measurement of the path length of the reflected light in time-of-flight measurements. Measurement of the distortion of a projection pattern in structured light methods.

Figure 3

Measurement setup with two Kinect v2 cameras facing each other. The subject sits on a chair without a backrest and breathes through a reference spirometer. The image is taken from [43], licensed via Creative Commons License, and not changed for this work.

Figure 4

Selection of a region of interest for depth-based plethysmography: (a) Subdivision into three subregions: pulmonary rib cage (blue), abdominal rib cage (green), and the abdomen (orange). White dots represent attached markers. Image taken from [56], licensed via Creative Commons License and cropped for this work.; (b) Subregions in lateral view: upper thorax (UT), lower thorax (LW), upper abdomen (UA), lower abdomen (LA). Image taken from [21], licensed via Creative Commons Attribution License and cropped for this work.

Figure 5

Determination of the final region of interest (ROI) as a selection of subregions. The areas are color coded with their corresponding amplitude strength from orange (strong) to blue (weak). Image taken from [55], licensed via Creative Commons Attribution License and not changed for this work.

Figure 6

Flow chart for non-contact determination of respiratory parameters. On the left, a depth image with a region of interest (ROI, red) on the chest and subROI on the neck (green). The acquired data is preprocessed and then transformed into a model. Optionally, patient data can be added to the model. In a training session, the error is minimized with ground truth.

Figure 7

Comparison of six different methods for determining respiration rate. Principal component analysis (PCA) from the raw signal of the region of interest (ROI). Mean of ROI (Mean Raw), the median of ROI (Median Raw). Use of a reference plane to subtract motion about the mean (Diff Mean) and median (Diff Median). Application of an own model with the help of a reference plane (Diff Model). Figure taken from [41], licensed via Creative Commons Attribution License and not changed for this work.