# Measurement of Head-Related Transfer Functions: A Review
## 7 Discussion
### Considerations and Trends in HRTF Measurements  
Various measurement systems including the hardware design and algorithms have been developed mainly to reduce the measurement time, which is a critical point when measuring HRTFs for human subjects. The use of \"reciprocity method\" can measure multi-directional HRTFs within only a few seconds, but the measurement accuracy is generally lower than with the \"direct measurement method\". Moreover, a large microphone array is required for the fast measurement (see Section 3.3). The use of large loudspeaker setups (spherical loudspeaker array, M\({}_{\text{A}}\), M\({}_{\text{P}}\)) can accelerate the measurement process, but the cost of the hardware construction is relatively high. As a compromise between the measuring time and the cost-benefit, a hybrid combination consisting of a loudspeaker array (multiple-loudspeakers mounted on a vertical, horizontal, or circular arc, \(\mathrm{M_{B}}\)-\(\mathrm{M_{L}}\) \(\mathrm{M_{L}}\)-\(\mathrm{M_{O}}\)) and a single-axis positioning system is commonly applied for the HRTF measurement in acoustic laboratories. Different measurement points can be covered with either rotating the subject or the loudspeaker array. The continuous mechanism is able to further accelerate the measurement process compared to the step-wise mechanism, but a suitable rotational speed needs to be chosen to ensure high measurement accuracy. It is obvious that a multi-loudspeaker-based system requires an expensive infrastructure (e.g., loudspeaker array and positioning system) and a large measurement space. To reduce the cost of the hardware setup, HMD-based fast measurement systems have been developed to fast measure HRTFs with only a single loudspeaker (\(\mathrm{S_{H}}\)-\(\mathrm{S_{K}}\)). In comparison with other measurement systems, a high computational load is required to provide users with the visual information (movement pattern, target measurement points, quality of calculated HRTFs) in real time. Furthermore, the measurement accuracy is highly dependent on the speed of head movement, which can not be controlled during the measurement. The benefit of the measurement system lies in the low cost of the infrastructure and the flexible setup, and this approach shows the potential for the individual HRTF measurement in home environments. For the measurement of highly accurate and repeatable HRTF datasets of human subjects, multi-loudspeaker-based measurement systems are still preferred. With the increased interest in 6-DoF binaural rendering applications, distance-dependent near-field HRTFs are urgently needed. Though there is no major difference between the methods for measuring near- and far-field HRTFs, an optimal sound source for measuring near-field HRTFs should be designed. Many acoustic laboratories constructed multi-loudspeaker systems for measuring HRTFs with a fixed source-listener distance, and these systems can not be flexibly used for measuring distance-dependent HRTFs. The measurement setup proposed by [PERSON] et al. [127] (see \(\mathrm{M_{I}}\)) is therefore recommended for the measurement of distance-dependent HRTFs with various distances, where multiple loudspeakers are mounted on a vertical locating loop with length-adjustable support rods. The torso can act as a shield or a reflector depending on the HATO and source directions, and shows noticeable influences on measured HRTFs [185; 208]. [PERSON] et al. [209] demonstrated the audible deviations of HRTFs measured with fixed and variable HATOs. Nowadays, many 3D audio reproduction systems have the ability to track the head and torso orientations using camera-based tracking systems, and HRTF datasets with multiple HATOs [174] can therefore be important for creating immersive VAEs. Such a dataset requires repeated measurements with various HATOs, and there is currently no efficient way to speed up the measurement procedure. Hence, some suitable interpolation methods as proposed in [209] can be used to reduce the number of measurements.