Abstract: An example communication method includes receiving a first synchronization signal block (SSB) from a network device. The first SSB is one of P SSBs, the P SSBs belong to a same synchronization signal burst set, and P is an integer greater than 1. The method further includes sending a preamble sequence on a first random access occasion (RO) associated with the first SSB. The first RO is in a first PRACH resource or a second PRACH resource. The P SSBs are associated with ROs in the first PRACH resource in a first SSB index order, the P SSBs are associated with ROs in the second PRACH resource in a second SSB index order, and the first SSB index order is different from the second SSB index order.

Abstract: The invention discloses an objective and quantitative detection method for amblyopia by electroencephalogram (EEG). The method comprises the following steps: firstly, carry out binocular dichoptic viewing display, then design a visual evoked stimulation paradigm, establish a brain-computer interface platform, build a test interaction interface, next determine an amblyopia EEG quantitative index. By using a suppression coefficient (SI) to describe the binocular suppression relationship, quantify the degree of amblyopia, and finally obtain amblyopia detection result feedback, where the computer interaction interface module presents a final amblyopia detection result to realize feedback of a user. The operation is simple and rapid, the applicability is high, and the indexes are objective and quantitative.

Abstract: The invention discloses an objective and quantitative detection method for amblyopia by electroencephalogram (EEG). The method comprises the following steps: firstly, carry out binocular dichoptic viewing display, then design a visual evoked stimulation paradigm, establish a brain-computer interface platform, build a test interaction interface, next determine an amblyopia EEG quantitative index. By using a suppression coefficient (SI) to describe the binocular suppression relationship, quantify the degree of amblyopia, and finally obtain amblyopia detection result feedback, where the computer interaction interface module presents a final amblyopia detection result to realize feedback of a user. The operation is simple and rapid, the applicability is high, and the indexes are objective and quantitative.