diff --git a/docs/source/eFeatures.rst b/docs/source/eFeatures.rst
index 9b9314c..4e72c01 100644
--- a/docs/source/eFeatures.rst
+++ b/docs/source/eFeatures.rst
@@ -2574,8 +2574,10 @@ See voltage clamp example for more details.
 
     # keep trace going from stim_start to voltage max
     max_idx = np.argmax(voltage_interval)
-    time_interval = time_interval[:max_idx + 1]
-    voltage_interval = voltage_interval[:max_idx + 1]
+    min_idx = np.argmin(voltage_interval[:max_idx + 1])
+    t_duration = time_interval[max_idx] - time_interval[min_idx]
+    time_interval = time_interval[min_idx:max_idx + 1]
+    voltage_interval = voltage_interval[min_idx:max_idx + 1]
 
     # correct time so that it starts from 0
     time_interval -= time_interval[0]
@@ -2585,11 +2587,14 @@ See voltage clamp example for more details.
         exp_fit,
         time_interval,
         voltage_interval,
-        p0=(1., voltage_interval[-1], voltage_interval[0] - voltage_interval[-1]),
+        p0=(1., voltage_interval[-1], np.min(voltage_interval) - voltage_interval[-1]),
         bounds=((0, -np.inf, -np.inf), (np.inf, np.inf, 0)),  # positive tau, negative A1
         nan_policy="omit",
     )
-    time_constant =  np.array([abs(popt[0])])
+    time_constant = np.array([abs(popt[0])])
+    # correction for very large values dur to noisy data
+    if abs(popt[0]) > 10 * t_duration:
+        time_constant = np.array([t_duration])
 
 deactivation_time_constant
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/efel/pyfeatures/pyfeatures.py b/efel/pyfeatures/pyfeatures.py
index 4e7386b..790b907 100644
--- a/efel/pyfeatures/pyfeatures.py
+++ b/efel/pyfeatures/pyfeatures.py
@@ -27,11 +27,15 @@
 """
 from efel.pyfeatures.cppfeature_access import _get_cpp_data, get_cpp_feature
 from efel.pyfeatures.isi import *
+import logging
 from typing_extensions import deprecated
 
 import numpy as np
 from numpy.fft import *
 
+
+logger = logging.getLogger(__name__)
+
 all_pyfeatures = [
     'voltage',
     'time',
@@ -390,8 +394,13 @@ def activation_time_constant() -> np.ndarray | None:
 
     # keep trace going from stim_start to voltage max
     max_idx = np.argmax(voltage_interval)
-    time_interval = time_interval[:max_idx + 1]
-    voltage_interval = voltage_interval[:max_idx + 1]
+    min_idx = np.argmin(voltage_interval[:max_idx + 1])
+    t_duration = time_interval[max_idx] - time_interval[min_idx]
+    if t_duration == 0:
+        logger.debug("Activation time constant: interval duration is 0, returning [0]")
+        return np.array([0.0])
+    time_interval = time_interval[min_idx:max_idx + 1]
+    voltage_interval = voltage_interval[min_idx:max_idx + 1]
 
     # correct time so that it starts from 0
     time_interval -= time_interval[0]
@@ -416,6 +425,15 @@ def activation_time_constant() -> np.ndarray | None:
     except (ValueError, RuntimeError):
         return None
 
+    if abs(popt[0]) > 10 * t_duration:
+        logger.debug(
+            "Activation time constant: unexpected time constant value (%s) "
+            "for smaller interval duration (%s), returning interval duration",
+            abs(popt[0]),
+            t_duration,
+        )
+        return np.array([t_duration])
+
     return np.array([abs(popt[0])])
 
 
diff --git a/tests/test_pyfeatures.py b/tests/test_pyfeatures.py
index c13733f..8c22f53 100644
--- a/tests/test_pyfeatures.py
+++ b/tests/test_pyfeatures.py
@@ -403,11 +403,11 @@ def test_activation_time_constant():
     feats = efel.get_feature_values(traces, ["activation_time_constant"])
     act_tau = [feat_dict["activation_time_constant"][0] for feat_dict in feats]
     act_tau_ref = [
-        4.430965e-02, 6.308063e-02, 1.354392e+00, 8.766326e-08,
-        1.556848e-06, 1.087861e+02, 3.513249e+01, 1.017114e+01,
-        4.616776e+00, 2.836394e+00, 1.972983e+00, 1.590110e+00,
-        1.21969111e+00, 1.07930254e+00, 8.55734307e-01, 7.39074539e-01,
-        6.58848184e-01, 5.96009883e-01
+        0.3026084023253483, 0.06597094092104987, 0.09179018404730191,
+        0.20514886735773108, 0.13922091324594776, 110.55045560417942,
+        35.48842150253384, 9.878098476029532, 4.391423684073282, 2.6753411591580787,
+        1.8958411673573918, 1.5901099575473472, 1.2196911091114777, 1.0793025478535727,
+        0.8557343061582321, 0.7390745386928983, 0.6588481846679133, 0.596009882583066,
     ]
     numpy.testing.assert_allclose(act_tau, act_tau_ref, rtol=1e-6, atol=1e-10)