Scholarlink

<p>Accurate diagnosis and monitoring of recovery after stroke are critical for effective motor rehabilitation. As stroke is inherently associated with impaired cerebral blood flow, functional near-infrared spectroscopy (fNIRS) provides a valuable tool for assessing hemodynamic changes in the brain. When combined with electroencephalography (EEG), this multimodal approach can provide complementary insights into neural and vascular responses during recovery. However, longitudinal datasets combining fNIRS and EEG in stroke populations remain limited. The current article presents an open access dataset with simultaneous fNIRS and EEG recordings from 16 post-stroke patients over 84 rehabilitation sessions. Participants performed motor tasks with both paretic and intact hands. The dataset includes raw and processed signals, clinical scores (ARAT, Fugl-Meyer) and patient demographics. This resource supports research into stroke recovery, development of neurorehabilitation strategies and fNIRS-based brain computer interfaces (BCI).</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Multisession fNIRS-EEG data of Post-Stroke Motor Recovery. Recordings During Intact and Paretic Hand Movements

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月14日

查看全文
  • Alexandra Medvedeva,
  • Nikolay Syrov,
  • Lev Yakovlev,
  • Yana Alieva,
  • Artemiy Berkmush-Antipova,
  • Galina Ivanova,
  • Natalia Shusharina,
  • Alexander Kaplan

摘要

Accurate diagnosis and monitoring of recovery after stroke are critical for effective motor rehabilitation. As stroke is inherently associated with impaired cerebral blood flow, functional near-infrared spectroscopy (fNIRS) provides a valuable tool for assessing hemodynamic changes in the brain. When combined with electroencephalography (EEG), this multimodal approach can provide complementary insights into neural and vascular responses during recovery. However, longitudinal datasets combining fNIRS and EEG in stroke populations remain limited. The current article presents an open access dataset with simultaneous fNIRS and EEG recordings from 16 post-stroke patients over 84 rehabilitation sessions. Participants performed motor tasks with both paretic and intact hands. The dataset includes raw and processed signals, clinical scores (ARAT, Fugl-Meyer) and patient demographics. This resource supports research into stroke recovery, development of neurorehabilitation strategies and fNIRS-based brain computer interfaces (BCI).