A training apparatus comprising: an acquisition unit that, while a subject is performing a behavior, is configured to acquire time-series myoelectric potentials of each of muscles 1, 2,..., m of the subject; a synergy calculation unit that is configured to calculate a muscle synergy matrix W, a control matrix C and an error matrix E from a myoelectric potential matrix M so that the relationship M = WC + E is satisfied, row vectors each expressing the acquired time-series myoelectric potentials of a corresponding one of the muscles 1, 2,..., m being arranged in rows in the myoelectric potential matrix M, n unit column vectors W, W,..., W (n) being arranged in columns in the muscle synergy matrix W, n row vectors C, C,..., C (n) being arranged in rows in the control matrix C; a feature quantity calculation unit that is configured to calculate a first feature quantity indicating consistency among the unit column vectors W, W,..., W (n) included in the calculated muscle synergy matrix W; and an output unit that is configured to output the calculated first feature quantity, characterized in that the synergy calculation unit is configured to apply non-negative matrix factorization, the first feature quantity is calculated through computation of inner product p(x,y) of row vectors x, y, and the first feature quantity is expressed as a feature quantity of 2/[n(n+2)]×∑ i=1 n ∑ j=1 n, j≠i p(W (i),W (j)), wherein the first feature quantity is a numeric value which increases as a proficiency level of the subject in the behavior increases, and the first feature quantity for a healthy person becomes larger than or equal to a first predetermined threshold. an acquisition unit that, while a subject is performing a behavior, is configured to acquire time-series myoelectric potentials of each of muscles 1, 2,..., m of the subject; a synergy calculation unit that is configured to calculate a muscle synergy matrix W, a control matrix C and an error matrix E from a myoelectric potential matrix M so that the relationship M = WC + E is satisfied, row vectors each expressing the acquired time-series myoelectric potentials of a corresponding one of the muscles 1, 2,..., m being arranged in rows in the myoelectric potential matrix M, n unit column vectors W, W,..., W (n) being arranged in columns in the muscle synergy matrix W, n row vectors C, C,..., C (n) being arranged in rows in the control matrix C; a feature quantity calculation unit that is configured to calculate a first feature quantity indicating consistency among the unit column vectors W, W,..., W (n) included in the calculated muscle synergy matrix W; and an output unit that is configured to output the calculated first feature quantity, characterized in that the synergy calculation unit is configured to apply non-negative matrix factorization, the first feature quantity is calculated through computation of inner product p(x,y) of row vectors x, y, and the first feature quantity is expressed as a feature quantity of 2/[n(n+2)]×∑ i=1 n ∑ j=1 n, j≠i p(W (i),W (j)), wherein the first feature quantity is a numeric value which increases as a proficiency level of the subject in the behavior increases, and the first feature quantity for a healthy person becomes larger than or equal to a first predetermined threshold.