update: tpt

src/NeuroAnalyzer.jl

@@ -241,6 +241,7 @@ include("internal/map_channels.jl")
 include("internal/markers.jl")
 include("internal/misc.jl")
 include("internal/ml.jl")
+include("internal/peaks.jl")
 include("internal/plots.jl")
 include("internal/recorder.jl")
 include("internal/reflect_chop.jl")

src/analyze/tpt.jl

@@ -25,14 +25,19 @@ function tpt_detect(obj::NeuroAnalyzer.NEURO)::Vector{Int64}
     acc_y = obj.data[5, :, :][:]
     acc_z = obj.data[6, :, :][:]
 
-    p_idx_x, _ = findpeaks1d(pos_x, distance=(sr(obj) ÷ 2), height=mean(pos_x) + 2*std(pos_x))
-    p_idx_y, _ = findpeaks1d(pos_y, distance=(sr(obj) ÷ 2), height=mean(pos_y) + 2*std(pos_y))
-    p_idx_z, _ = findpeaks1d(pos_z, distance=(sr(obj) ÷ 2), height=mean(pos_z) + 2*std(pos_z))
-    p_idx_acc_x, _ = findpeaks1d(acc_x, distance=(sr(obj) ÷ 2), height=mean(acc_x) + 2*std(acc_x))
-    p_idx_acc_y, _ = findpeaks1d(acc_y, distance=(sr(obj) ÷ 2), height=mean(acc_y) + 2*std(acc_y))
-    p_idx_acc_z, _ = findpeaks1d(acc_z, distance=(sr(obj) ÷ 2), height=mean(acc_z) + 2*std(acc_z))
-
-    p_idx = round.(Int64, p_idx_x)
+    t = obj.time_pts
+
+    p_idx_x = _tpt_peaks(pos_x, t)
+    p_idx_y = _tpt_peaks(pos_y, t)
+    p_idx_z = _tpt_peaks(pos_z, t)
+    p_idx_acc_x = _tpt_peaks(acc_x, t)
+    p_idx_acc_y = _tpt_peaks(acc_y, t)
+    p_idx_acc_z = _tpt_peaks(acc_z, t)
+
+    p_idx = unique(sort(union(p_idx_x, p_idx_y, p_idx_acc_x, p_idx_acc_y)))
+    tx = t[p_idx]
+    tx = [tx[1]; diff(tx)]
+    p_idx = p_idx[tx .>= 0.2]
 
     _info("Detected pinches: $(length(p_idx))")
 

src/gui/iview.jl

@@ -1230,7 +1230,7 @@ Nothing
 """
 function iview(obj1::NeuroAnalyzer.NEURO, obj2::NeuroAnalyzer.NEURO; zoom::Real=10)::Nothing
 
-    (signal_len(obj1) / sr(obj1)) < zoom && (zoom = round(obj1.time_pts[end]) / 2)
+    obj1.time_pts[end] < zoom && (zoom = round(obj1.time_pts[end]) / 2)
 
     @assert size(obj1) == size(obj2) "Both signals must have the same size."
     @assert obj1.header.recording[:channel_order] == obj2.header.recording[:channel_order] "Both signals must have the same order."

src/internal/peaks.jl

@@ -0,0 +1,16 @@
+function _tpt_peaks(x::AbstractVector, t::AbstractVector)::Vector{Int64}
+    x[x .< 0] .= 0
+    x = diff(x)
+    t = t[1:end-1]
+    x[x .< 0] .= 0
+    #x = derivative(x)
+    dx = env_up(x, d=4, t)
+    verbose_tmp = NeuroAnalyzer.verbose
+    NeuroAnalyzer.verbose = false
+    f = filter_create(fprototype=:fir, ftype=:lp, cutoff=15, n=length(dx), fs=50, order=8)
+    NeuroAnalyzer.verbose = verbose_tmp
+    dx = filter_apply(dx, flt=f)
+    p_idx, _ = findpeaks1d(dx, distance=10, height=mean(dx) + 0.25 * std(dx))
+    # p_idx, _ = findpeaks1d(dx2, distance=(sr(obj) ÷ 4), height=mean(dx) + 1.5 * std(dx))
+    return p_idx
+end

src/tester/tpt.jl

@@ -188,6 +188,7 @@ function tpt(; duration::Int64=20, port_name::String="/dev/ttyUSB0")::NeuroAnaly
     # sampling rate is 50 Hz = 20 ms per loop
     fs = 50
     t = collect(0:1/fs:duration)
+    t = t[1:(end - 1)]
     tpt_ch_x = zeros(length(t))
     tpt_ch_y = zeros(length(t))
     tpt_ch_z = zeros(length(t))
@@ -218,7 +219,6 @@ function tpt(; duration::Int64=20, port_name::String="/dev/ttyUSB0")::NeuroAnaly
     println()
     println()
     println("Testing completed")
-
     tpt_signal = Matrix([tpt_ch_x tpt_ch_y tpt_ch_z tpt_ch_accx tpt_ch_accy tpt_ch_accz]')
     tpt_signal = reshape(tpt_signal, 6, :, 1)