activity
20182026
most citedA Hidden Markov Model Based Unsupervised Algorithm for Sleep/Wake Identification Using Actigraphy

65 citations · 66 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2026

Who Is in Mind Matters: Attachment Representations in Early Childhood Synchronize Child-Adult Interacting Brains

Ruxin Su, Jiayang Xu, Saishuang Wu +9

Human attachment is distinguished by enduring internalized representations that shapes neurodevelopment and social-emotional functioning. However, as unobservable inner processes m…

q-bio.NC2024★ 1 cited

Theta and/or alpha? Neural oscillational substrates for dynamic inter-brain synchrony during mother-child cooperation

Jiayang Xu, Yamin Li, Ruxin Su +9

Mother-child interaction is a highly dynamic process neurally characterized by inter-brain synchrony (IBS) at θ and/or α rhythms. However, their establishment, dynamic changes, and…

stat.ME2024

An Efficient Two-Dimensional Functional Mixed-Effect Model Framework for Repeatedly Measured Functional Data

Cheng Cao, Jiguo Cao, Hao Pan +3

With the rapid development of wearable device technologies, accelerometers can record minute-by-minute physical activity for consecutive days, which provides important insight into…

q-bio.NC2023

Inter-brain substrates of role switching during mother-child interaction

Yamin Li, Saishuang Wu, Jiayang Xu +8

Mother-child interaction is highly dynamic and reciprocal. Switching roles in these back-and-forth interactions serves as a crucial feature of reciprocal behaviors while the underl…

stat.AP2018★ 65 cited

A Hidden Markov Model Based Unsupervised Algorithm for Sleep/Wake Identification Using Actigraphy

Xinyue Li, Yunting Zhang, Fan Jiang +1

Actigraphy is widely used in sleep studies but lacks a universal unsupervised algorithm for sleep/wake identification. In this study, we proposed a Hidden Markov Model (HMM) based…