Quantitative assessment of human sensitivity of scanning in lump detection

Abstract

Palpation is an important medical procedure that uses the human tactile feedback to identify and diagnose the internal structures of a patient. An important aspect of palpation is detecting and localizing hard lumps in soft tissue which is used to detect subsurface tumors in the breasts and prostate for example. A deeper understanding of the lump detection process will allow for the improvement of current procedures and training, and furthermore aid the development of artificial tactile feedback systems. Thus far the quantification of human sensitivity in lump detection oversimplified the lump detection palpating strategy as an indentation. However, actual palpation strategy of lump detection is an amalgam of haptic exploration strategies more resembling scanning rather than indentation. In this thesis, the human performance in scanning lump detection is evaluated in terms of the minimum indentation depth required for lump detection. Firstly, a psychophysics experiment is conducted using a phantom tissue with a hard inclusion to measure the minimum indentation depth required for detection in scanning and indentation respectively using the method of limits. The psychophysics experiments showed that the scanning can reduce the indentation depth by up to 80% by increasing the lateral motion speed during scanning. Secondly, lump detection sensitivity of scanning is evaluated in terms of lateral forces evolved during scanning under various speeds. Data showed that neither absolute value of the lateral force nor the rate of its change was the cue for lump detection.