PROBLEM TO BE SOLVED: To provide a swallowing function evaluation method and a swallowing function evaluation apparatus capable of determining the voluntary swallowing strength and a difference of a single swallowing amount, a difference of physical properties (hardness, viscosity, temperature, liquid, individual) of food and a food bolus, a difference of a swallowing state and a presence of aspiration, types (overt aspiration, occult aspiration, aspiration before swallowing, aspiration during swallowing, aspiration after swallowing, etc), and a risk (larynx inflow, etc).SOLUTION: A swallowing function evaluation method of the present invention is characterized by: detecting at least a biological signal from swallowing start to swallowing completion； extracting a feature amount from the detected biological signal； identifying a swallowing state from the feature amount by using machine learning, and evaluating a swallowing function； using a suprahyoid muscle group biological signal by the muscle activities of the suprahyoid muscle group and an infrahyoid muscle group biological signal by the muscle activities of the infrahyoid muscle group as the biomedical signal； and extracting the feature amount from the suprahyoid muscle group biological signal and the infrahyoid muscle group biological signal.SELECTED DRAWING: Figure 1COPYRIGHT: (C)2020,JPO&INPIT【課題】随意嚥下の強さや一回嚥下量の違い、食物や食塊の物性値（硬さ、粘度、温度、液体、個体など）の違いなど、嚥下状態の違いや誤嚥の有無・種類（顕性誤嚥、不顕性誤嚥、嚥下前誤嚥、嚥下中誤嚥、嚥下後誤嚥など）・リスク（喉頭流入など）を判別できる嚥下機能評価法及び嚥下機能評価装置を提供すること。【解決手段】本発明の嚥下機能評価法は、少なくとも嚥下開始から嚥下終了までの生体信号を検出し、検出した生体信号から特徴量を抽出し、機械学習を用いて特徴量から嚥下状態を識別して嚥下機能を評価し、生体信号として、舌骨上筋群の筋活動による舌骨上筋群生体信号と、舌骨下筋群の筋活動による舌骨下筋群生体信号とを用い、舌骨上筋群生体信号と舌骨下筋群生体信号とから特徴量を抽出することを特徴とする。【選択図】 図１
