The technique of sequential pattern mining means generating a set of inter-transaction patterns residing in time-dependent data. This paper proposes a new method for generating sequential patterns with the use of Hellinger measure. While the current methods are generating single dimensional sequential patterns within a single attribute, the proposed method is able to detect multi-dimensional patterns among different attributes. A number of heuristics, based on the characteristics of Hellinger measure, are proposed to reduce the computational complexity of the sequential pattern systems. Some experimental results are presented.