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小枝　正汰 (サエダ　シヨウタ)

電子科学研究所　生命科学研究部門助教

生体信号処理、医療データ解析、機械学習を専門とし、医療AIの研究に取り組んでいます。


名古屋大学大学院博士後期課程では、孤発性レム睡眠行動障害を対象に、心拍変動を用いた自律神経機能異常の定量評価と病態識別モデルの開発を進めました。研究留学先のスタンフォード大学では、多施設データを用いた国際共同研究に従事し、睡眠ポリグラフ検査データからレム睡眠行動障害とその他の睡眠障害を鑑別するAIモデルの開発に携わりました。


現在は、北海道大学電子科学研究所の助教として、睡眠医学および循環器領域を対象に、生体信号に内在する臨床的に重要な情報を工学的手法によって抽出し、医療現場で活用可能な診断支援技術へとつなげる研究を行っています。低侵襲かつ解釈性の高い医療AIの実装を目指しています。

研究者基本情報

■ 学位
  • 博士(工学), 名古屋大学, 2026年03月
■ URL
researchmap URLホームページURL■ ID 各種
研究者番号
  • 51037362
ORCID IDJ-Global ID■ 研究キーワード・分野
研究キーワード
  • レム睡眠行動障害
  • レビー小体病
  • 睡眠障害
  • 心拍変動解析
  • 生体信号処理
  • 医療データ解析
研究分野
  • 情報通信, 生命、健康、医療情報学
  • ライフサイエンス, 医用システム

経歴

■ 経歴
経歴
  • 2026年04月 - 現在
    北海道大学, 電子科学研究所, 助教, 日本国
  • 2025年04月 - 2026年01月
    スタンフォード大学医学部, Department of Psychiatry and Behavioral Science School of Medicine, 客員研究員, アメリカ合衆国
学歴
  • 2023年04月 - 2026年03月, 名古屋大学, 大学院工学研究科, 物質プロセス工学専攻, 博士後期課程, 日本国
  • 2021年04月 - 2023年03月, 名古屋大学, 大学院工学研究科, 物質プロセス工学専攻, 博士前期課程, 日本国
  • 2017年04月 - 2021年03月, 名古屋大学, 工学部, マテリアル工学科, 日本国
  • 2014年04月 - 2017年07月, 愛知県立西春高等学校

研究活動情報

■ 受賞
  • 2024年09月, EMBS Japan Chapter, IEEE EMBS East and Central Japan Chapter/West Japan Chapter Young Researcher Award
    Heart rate variability-based Model for estimating the severity of orthostatic hypotension in patients with REM sleep behavior disorder
  • 2022年03月, 名古屋大学, 修士中間発表 優秀賞
■ 論文
  • IoT-Based Atrial Fibrillation Screening System, Development, and Prospective Study.
    Koichi Fujiwara; Tetsuma Kawaji; Shota Saeda; Toshitaka Yamakawa; Masashi Kato; Takanori Aizawa; Takafumi Yokomatsu; Shinji Miki
    IEEE Internet of Things Journal, 12, 11, 17661, 17673, 2025年06月
    研究論文（学術雑誌）
  • Blunted tachycardia and cardiac sympathetic denervation in isolated rapid eye movement sleep behavior disorder.
    Shota Saeda; Yukiyoshi Sumi; Koichi Fujiwara; Hiroshi Kadotani
    BMC neurology, 24, 1, 317, 317, 2024年09月04日, ［国際誌］
    英語, 研究論文（学術雑誌）, BACKGROUND: Isolated rapid eye movement sleep behavior disorder (iRBD) serves as a prodromal phase of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Blunted tachycardia (BT) during postural changes indicates neurogenic orthostatic hypotension, a marker of autonomic dysfunction. We aimed to investigate whether BT is associated with cardiac sympathetic neurogenic denervation. Additionally, we conducted a preliminary short-term follow-up to examine the potential prognostic significance of BT regarding phenoconversion and mortality. METHODS: Forty-three patients with iRBD at Shiga University of Medical Science Hospital underwent active standing tests to identify BT, defined by a specific ratio of decrease in systolic blood pressure to inadequate increase in heart rate after standing, and orthostatic hypotension. 123I-metaiodobenzylguanidine myocardial scintigraphy (123I-MIBG) and dopamine transporter single-photon emission computed tomography (DAT-SPECT) were performed. Participants were followed up for 3.4 ± 2.4 years for phenoconversion and 4.0 ± 2.3 years for mortality assessment, and the risk of events was analyzed using log-rank tests. RESULTS: Among the 43 participants (mean age, 72.3 ± 7.9 years; 8 female), 17 met the BT criteria. We found no significant comorbidity-related differences in hypertension or diabetes between the BT(+) and BT(-) groups. Orthostatic hypotension was more prevalent in the BT(+) group than in the BT(-) group (47.1% vs 7.7%, p = 0.003). BT(+) patients were older with a lower early and delayed MIBG uptake; however, no significant differences were observed in DAT accumulation. Phenoconversion was observed in seven (41.2%) BT(+) and seven (26.9%) BT(-) patients. Three deaths were recorded in the BT(+) group (17.6%) and three in the BT(-) group (11.5%). No significant differences were observed in the risk of phenoconversion or mortality between the groups. CONCLUSIONS: We have identified the possibility that BT reflects cardiac sympathetic neurogenic denervation in patients with iRBD. Future research is needed to elucidate the potential prognostic value of BT.
  • Heart rate variability-based Model for estimating the severity of orthostatic hypotension in patients with REM sleep behavior disorder.
    Shota Saeda; Koichi Fujiwara; Yukiyoshi Sumi; Hiroshi Kadotani
    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2024, 1, 4, 2024年07月, ［国際誌］
    英語, 研究論文（学術雑誌）, BACKGROUND: Orthostatic hypotension (OH) is a typical autonomic dysfunction in patients with idiopathic REM sleep behavior disorder (iRBD). The Schellong test is a well-known method to evaluate the presence of OH; however, it is burdensome for both patients and the medical staff from the viewpoint of ensuring patient safety. In this study, we developed a machine learning (ML) model to discriminate the presence or absence of OH based on heart rate variability (HRV) in the supine position. METHODS: We recruited elderly healthy participants (HC) and iRBD patients and measured participants' R-R interval (RRI) during the Schellong test. The HRV features were calculated from the RRIs and were used as inputs for the ML model. We trained an ML model that combines two binary classifiers. The first model classifies HC and iRBD, and the second model discriminates the classified patients with iRBD between OH(-) and OH(+). RESULTS: The macro average classification performance was accuracy of 81%, recall of 73%, precision of 82%, and F-measure of 68%. In addition, the sensitivity for OH(+)iRBD was 100%. CONCLUSION: Utilizing this ML model will help to reduce the burden of the Schellong test.
  • Heat illness detection with heart rate variability analysis and anomaly detection algorithm.
    Koichi Fujiwara; Koshi Ota; Shota Saeda; Toshitaka Yamakawa; Takatomi Kubo; Aozora Yamamoto; Yuki Maruno; Manabu Kano
    Biomedical Signal Processing and Control, 87, Part A, 105520, 105520, 2024年01月
    研究論文（学術雑誌）
  • Effects of pleasant sound on overnight sleep condition: A crossover randomized study.
    Shota Saeda; Koichi Fujiwara; Takafumi Kinoshita; Yukiyoshi Sumi; Masahiro Matsuo; Kiyoshi Yamaki; Takahiro Kawashima; Hiroshi Kadotani
    Frontiers in sleep, 1, 986333, 986333, 2022年, ［国際誌］
    英語, 研究論文（学術雑誌）, It is desirable to improve sleep quality since poor sleep results in decreases in work productivity and increases in risks of lifestyle-related diseases. Sleep spindles in sleep EEG are waveforms that characterize non-REM sleep Stage 2 (Stage N2). Music therapy has been adopted as a non-pharmacological therapy for sleep quality improvement; however, few studies mention the relationship between music during sleep and spindles. We conducted a crossover randomized study to investigate music's effects on spindles and sleep parameters. Polysomnography (PSG) was performed on 12 adult males with sleep difficulties over three nights, during which they were exposed to three different acoustic environments-silent, white noise, and pleasant sounds-throughout the night, in a crossover randomized setting. Half of the participants with large WASO were defined as the sleep maintenance difficulty group. We investigated whether pleasant sounds shortened sleep onset latency (SOL) and increased the number of spindles (SN) and spindle density (SD) compared to white noise, using silent as the reference. The spindles were detected using the previously reported automatic spindle detection algorithm. After one patient was excluded due to data corruption, a total of 11 participants, including the sleep maintenance difficulty group (n = 5), were analyzed. For all participants, SOL was not significantly shorter with pleasant sound than with white noise (p = 0.683); for the sleep maintenance difficulty group, SOL tended to be shorter with pleasant sound than with white noise (p = 0.060). Compared to white noise, the SN increased in pleasant sound for 7 of 11 (4 of 5 in the sleep maintenance difficulty group), and SD increased for 5 of 11 (3 of 5 in the sleep maintenance difficulty group). The results suggest that all-night background sound exposure may affect SN and SD. Future research should investigate whether background sound exposure reduces sleep-related distress, achieves sound sleep, or improves daytime psychomotor function.
■ その他活動・業績
■ 講演・口頭発表等
  • レム睡眠行動障害患者が有する起立性低血圧の重症度を心拍変動指標に基づいて分類する機械学習モデルの開発
    小枝正汰; 藤原幸一; 角幸頼; 角谷寛
    第63回日本生体医工学会大会, 2024年, 口頭発表（一般）
  • Heart rate variability-based Model for estimating the severity of orthostatic hypotension in patients with REM sleep behavior disorder
    Shota Saeda; Koichi Fujiwara; Yukiyoshi Sumi; Hiroshi Kadotani
    46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024年, 口頭発表（一般）
  • 心拍変動解析を用いたレム睡眠行動障害患者における起立性低血圧を鑑別する機械学習モデルの開発
    小枝正汰; 藤原幸一; 角幸頼; 角谷寛
    第26回情報論的学習理論ワークショップ, 2023年, ポスター発表
  • Logistic Regression Model for Orthostatic Hypotension Detection in REM sleep behavior disorder Using Heart Rate Variability
    Shota Saeda; Koichi Fujiwara; Toshitaka Yamakawa; Yukiyoshi Sumi; Hiroshi Kadotani
    World Sleep 2023, 2023年
  • Development of Desktop App for Detecting Sleep Spindles from Sleep Electroencephalogram Data
    Shota Saeda; Koichi Fujiwara
    45th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society, 2023年, ポスター発表
  • 睡眠ポリグラフ検査に基づくうつ病と双極性障害の鑑別アルゴリズムの開発
    小枝正汰; 藤原幸一; 岩本邦弘; 宮田聖子; 尾崎紀夫
    日本睡眠学会第47回定期学術集会, 2022年, 口頭発表（一般）
  • Development of Heat Stroke Detection Model Based on Heart Rate Variability Using LSTM-AutoEncoder
    Shota Saeda; Koshi Ota; Koichi Fujiwara; Takatomi Kubo; Toshitaka Yamakawa; Aozora Yamamoto; Yuki Maruno; Manabu Kano
    Asia Pacific Signal and Information Processing Association Annual Summit and Conference 2022, 2022年, 口頭発表（一般）
  • Relationships between Environmental Sound and Sleep Quality Based on Sleep Spindles,
    Shota Saeda; Koichi Fujiwara; Yukiyoshi Sumi; Hiroshi Kadotani
    AROB-ISBC-SWARM 2022, 2022年, 口頭発表（一般）
  • ST-RUSを用いた睡眠脳波解析による異なる音環境下でのスピンドル出現の評価
    小枝正汰; 藤原幸一; 木下貴文; 角幸頼; 角谷寛; 山木清志; 森島守人; 川嶋隆宏
    日本睡眠学会第 46 回定期学術集会, 2021年
  • Relaxing Music Increases Sleep Spindles and Improve Sleep Quality
    Shota Saeda; Koichi Fujiwara; Yukiyoshi Sumi; Hiroshi Kadotani
    43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021年
■ 所属学協会
  • APSIPA
  • 人工知能学会
  • 日本睡眠学会
  • IEEE
  • 化学工学会