diff --git a/Snakefile b/Snakefile
index e98061fe..3e1647e9 100644
--- a/Snakefile
+++ b/Snakefile
@@ -44,6 +44,9 @@ rule all:
         expand("data/raw/{pid}/fitbit_{fitbit_sensor}_with_datetime.csv",
                             pid=config["PIDS"],
                             fitbit_sensor=config["FITBIT_SENSORS"]),
+        expand("data/processed/{pid}/fitbit_heartrate_{day_segment}.csv",
+                            pid = config["PIDS"],
+                            day_segment = config["HEARTRATE"]["DAY_SEGMENTS"]),
         expand("data/processed/{pid}/fitbit_step_{day_segment}.csv",
                             pid = config["PIDS"],
                             day_segment = config["STEP"]["DAY_SEGMENTS"]),
diff --git a/config.yaml b/config.yaml
index 377afd85..a30b8c4f 100644
--- a/config.yaml
+++ b/config.yaml
@@ -72,7 +72,6 @@ BLUETOOTH:
 GOOGLE_ACTIVITY_RECOGNITION:
   DAY_SEGMENTS: *day_segments
   METRICS: ['count','mostcommonactivity','countuniqueactivities','activitychangecount','sumstationary','summobile','sumvehicle']
-  
 
 BATTERY:
   DAY_SEGMENTS: *day_segments
@@ -92,6 +91,10 @@ ACCELEROMETER:
   DAY_SEGMENTS: *day_segments
   METRICS: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude", "ratioexertionalactivityepisodes", "sumexertionalactivityepisodes", "longestexertionalactivityepisode", "longestnonexertionalactivityepisode", "countexertionalactivityepisodes", "countnonexertionalactivityepisodes"]
 
+HEARTRATE:
+  DAY_SEGMENTS: *day_segments
+  METRICS: ["maxhr", "minhr", "avghr", "medianhr", "modehr", "stdhr", "diffmaxmodehr", "diffminmodehr", "entropyhr", "lengthoutofrange", "lengthfatburn", "lengthcardio", "lengthpeak"]
+
 STEP:
   DAY_SEGMENTS: *day_segments
   METRICS:
diff --git a/rules/features.snakefile b/rules/features.snakefile
index b10d8ace..1681e915 100644
--- a/rules/features.snakefile
+++ b/rules/features.snakefile
@@ -131,6 +131,17 @@ rule accelerometer_metrics:
     script:
         "../src/features/accelerometer_metrics.py"
 
+rule fitbit_heartrate_metrics:
+    input:
+        "data/raw/{pid}/fitbit_heartrate_with_datetime.csv",
+    params:
+        day_segment = "{day_segment}",
+        metrics = config["HEARTRATE"]["METRICS"],
+    output:
+        "data/processed/{pid}/fitbit_heartrate_{day_segment}.csv"
+    script:
+        "../src/features/fitbit_heartrate_metrics.py"
+
 rule fitbit_step_metrics:
     input:
         steps_data = "data/raw/{pid}/fitbit_steps_with_datetime.csv",
diff --git a/src/features/fitbit_heartrate_metrics.py b/src/features/fitbit_heartrate_metrics.py
new file mode 100644
index 00000000..26f50917
--- /dev/null
+++ b/src/features/fitbit_heartrate_metrics.py
@@ -0,0 +1,49 @@
+import pandas as pd
+import numpy as np
+from scipy.stats import entropy
+import json
+
+
+heartrate_data = pd.read_csv(snakemake.input[0], parse_dates=["local_date_time", "local_date"])
+day_segment = snakemake.params["day_segment"]
+metrics = snakemake.params["metrics"]
+
+
+heartrate_features = pd.DataFrame(columns=["local_date"] + ["heartrate_" + day_segment + "_" + x for x in metrics])
+if not heartrate_data.empty:
+    device_id = heartrate_data["device_id"][0]
+    num_rows_per_minute = heartrate_data.groupby(["local_date", "local_hour", "local_minute"]).count().mean()["device_id"]
+    if day_segment != "daily":
+        heartrate_data =heartrate_data[heartrate_data["local_day_segment"] == day_segment]
+    
+    if not heartrate_data.empty:
+        heartrate_features = pd.DataFrame()
+     
+        # get stats of heartrate
+        if "maxhr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_maxhr"] = heartrate_data.groupby(["local_date"])["heartrate"].max()
+        if "minhr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_minhr"] = heartrate_data.groupby(["local_date"])["heartrate"].min()
+        if "avghr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_avghr"] = heartrate_data.groupby(["local_date"])["heartrate"].mean()
+        if "medianhr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_medianhr"] = heartrate_data.groupby(["local_date"])["heartrate"].median()
+        if "modehr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_modehr"] = heartrate_data.groupby(["local_date"])["heartrate"].agg(pd.Series.mode)
+        if "stdhr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_stdhr"] = heartrate_data.groupby(["local_date"])["heartrate"].std()
+        if "diffmaxmodehr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_diffmaxmodehr"] = heartrate_data.groupby(["local_date"])["heartrate"].max() - heartrate_data.groupby(["local_date"])["heartrate"].agg(pd.Series.mode)
+        if "diffminmodehr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_diffminmodehr"] = heartrate_data.groupby(["local_date"])["heartrate"].agg(pd.Series.mode) - heartrate_data.groupby(["local_date"])["heartrate"].min()
+        if "entropyhr" in metrics:
+            heartrate_features["heartrate_" + day_segment + "_entropyhr"] = heartrate_data.groupby(["local_date"])["heartrate"].agg(entropy)
+
+        # get number of minutes in each heart rate zone
+        for feature_name in list(set(["lengthoutofrange", "lengthfatburn", "lengthcardio", "lengthpeak"]) & set(metrics)):
+            heartrate_zone = heartrate_data[heartrate_data["heartrate_zone"] == feature_name[6:]]
+            heartrate_features["heartrate_" + day_segment + "_" + feature_name] = heartrate_zone.groupby(["local_date"])["device_id"].count() / num_rows_per_minute
+
+        heartrate_features = heartrate_features.reset_index()
+
+heartrate_features.to_csv(snakemake.output[0], index=False)