R中时间序列数据的聚类

我希望这能让团队安全、健康。我正在研究一个涉及一系列频道集群的问题。 我有一个fNIRS数据集，它是在三种情况下，以大约4 hz的频率采样的-2到20秒的血液动力学响应函数，用于一系列49个通道。我想创建一个集群，考虑通道的响应功能和定位（大脑区域）（下面的SD变量）。然后，我想评估在任何集群中，条件、年龄或年龄与条件之间的交互是否存在显著的主要影响。我在下面创建了一个小型示例数据集

df1 <- data.frame(Participant = c('A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A',  'B', 'B','B','B','B''B', 'B','B','B','B','C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'  ), 
                  Time = c(1,2,3,4,5, 1,2,3,4,5, 1,2,3,4,5, 1,2,3,4,5, 1,2,3,4,5, 1,2,3,4,5), 
Condition = c(‘Happy’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Happy’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Sad’, ‘Sad’)
                  SD1 = c(-10,-10,-10,-10,-10,50, 50, 50,50,50,1,1, 1,1,1, -10,-10,-10,-10,-10,50, 50, 50,50,50,1,1, 1,1,1), 
                  SD2 = c(0, 50, 50, 50,0, 0,0,0,1,50, 0,0,0,1,50, 0, 5, 5, 5,0, 0,0,0,1,50, 0,0,0,1,50)
SD3 = c(-12,-12,-12,-12,-12,50, 50, 50,50,50,1,1, 1,1,1, 1,2,3,4,5, 1,2,3,4,5), 
                  SD4 = c(0, 100, 100, 100,0, 0,0,0,1,50, 0,0,0,1,50,2,3,4,5, 1,2,3,4,5, 1))


df2 <-data.frame(Participant = c(‘A’, ‘B’, ‘C’)
Age <- c(5, 6, 7)
Age2 <- c('young', 'young', 'old'))


df3 <- data.frame(SourceDetector c(‘SD1’, ‘SD2’, ‘SD3’, ‘SD4’)
    Location <- c(‘Front’, ‘Front’, ‘Front’, ‘Back’))

df1