臨床集団における社会的相互作用検出のためのスマートウォッチアルゴリズムとしてのSocialBitの検証
Amar Dhand1,2,3, Samuel Tate4, Cade Mack4
1Department of Neurology, Brigham and Women's Hospital, Boston, MA, 02115, USA. adhand@bwh.harvard.edu.
Scientific reports
|February 4, 2026
まとめ
新しいスマートウォッチアルゴリズムであるSocialBitは、周囲の音声を使用して社会的相互作用を正確に検出します。このツールは、神経学的患者の社会的関与を測定するためのプライバシーを保護する方法を提供し、回復のモニタリングを支援します。
科学分野:
- デジタルヘルス
- 神経科学
- 機械学習
背景:
- 社会的相互作用は、脳の健康と神経学的損傷からの回復にとって非常に重要です。
- 現在、社会的相互作用を測定する方法は、特に神経学的障害を持つ個人にとって、リアルタイムの能力が欠けています。
主な方法:
- 市販のスマートウォッチで周囲音の特徴を利用するプライバシー保護アルゴリズムであるSocialBitを開発しました。
- 153人の入院中の脳卒中患者を対象に8日間前向き検証研究を実施し、SocialBitと人間によるコーディングされたグラウンドトゥルースを比較しました。
- 多様な脳卒中の重症度、認知レベル、失語症のサブタイプにわたるパフォーマンスを評価しました。
結論:
- SocialBitは、多様な患者集団に適した、検証済みの正確な社会的相互作用のデジタルバイオマーカーです。
- このアルゴリズムは、遠隔モニタリング、臨床試験、および神経学的状態が社会的関与に与える影響の理解に役立つ可能性があります。
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