A human fatigue assessment device (100 400 600 1000 1200) comprising: a physiological signal measuring unit (101 401) configured to measure a pulse wave signal of a user; a feature value extracting unit (102 402 602 1002 1202) configured to extract first feature values each of which is obtained from a systolic posterior component of the pulse wave signal measured by said physiological signal measuring unit; a storage unit (103 403 603 1003 1203) in which the first feature values extracted by said feature value extracting unit are stored; and a fatigue determining unit (104 1204) configured to determine whether or not the user is fatigued, using the first feature values extracted by said feature value extracting unit, wherein said fatigue determining unit is configured to compare a first feature value among the first feature values extracted by said feature value extracting unit and at least one of the first feature values stored in said storage unit, to determine whether or not the user is fatigued, said feature value extracting unit (102 402 602 1002 1202) is configured to calculate an accelerated plethysmogram from the pulse wave signal, and to extract the first feature values, using information on at least a c wave or a d wave which is a component wave of an accelerated plethysmogram corresponding to the systolic posterior component. characterized in that said human fatigue assessment device further comprises a fatigue type determining unit (406 606 1006 1206) configured to determine a type of the fatigue of the user as to whether the fatigue is due to a first work type, namely difficult work, or due to a second work type, namely monotonous work, based on at least one additional feature value extracted by the feature value extracting unit (102 402 602 1002 1202), said at least one additional feature value obtained from, a second feature value indicating an amount of parasympathetic nerve activity, or from a brain signal related to at least one of a a or a β wave, namely a third feature value, and said at least one additional feature value comprising a tendency to change in value in response to one of the first or second work type, while not comprising said tendency in response to the respective second or first work type. a physiological signal measuring unit (101 401) configured to measure a pulse wave signal of a user; a feature value extracting unit (102 402 602 1002 1202) configured to extract first feature values each of which is obtained from a systolic posterior component of the pulse wave signal measured by said physiological signal measuring unit; a storage unit (103 403 603 1003 1203) in which the first feature values extracted by said feature value extracting unit are stored; and a fatigue determining unit (104 1204) configured to determine whether or not the user is fatigued, using the first feature values extracted by said feature value extracting unit, wherein said fatigue determining unit is configured to compare a first feature value among the first feature values extracted by said feature value extracting unit and at least one of the first feature values stored in said storage unit, to determine whether or not the user is fatigued, said feature value extracting unit (102 402 602 1002 1202) is configured to calculate an accelerated plethysmogram from the pulse wave signal, and to extract the first feature values, using information on at least a c wave or a d wave which is a component wave of an accelerated plethysmogram corresponding to the systolic posterior component. characterized in that said human fatigue assessment device further comprises a fatigue type determining unit (406 606 1006 1206) configured to determine a type of the fatigue of the user as to whether the fatigue is due to a first work type, namely difficult work, or due to a second work type, namely monotonous work, based on at least one additional feature value extracted by the feature value extracting unit (102 402 602 1002 1202), said at least one additional feature value obtained from, a second feature value indicating an amount of parasympathetic nerve activity, or from a brain signal related to at least one of a a or a β wave, namely a third feature value, and said at least one additional feature value comprising a tendency to change in value in response to one of the first or second work type, while not comprising said tendency in response to the respective second or first work type.