diff --git a/Snakefile b/Snakefile
index 3b57d270..5cfe9e44 100644
--- a/Snakefile
+++ b/Snakefile
@@ -235,8 +235,7 @@ for provider in config["FITBIT_HEARTRATE_SUMMARY"]["PROVIDERS"].keys():
 for provider in config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"].keys():
     if config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"][provider]["COMPUTE"]:
         files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_raw.csv", pid=config["PIDS"]))
-        files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_parsed.csv", pid=config["PIDS"]))
-        files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_parsed_with_datetime.csv", pid=config["PIDS"]))
+        files_to_compute.extend(expand("data/raw/{pid}/fitbit_heartrate_intraday_with_datetime.csv", pid=config["PIDS"]))
         files_to_compute.extend(expand("data/interim/{pid}/fitbit_heartrate_intraday_features/fitbit_heartrate_intraday_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"][provider]["SRC_LANGUAGE"].lower(), provider_key=provider.lower()))
         files_to_compute.extend(expand("data/processed/features/{pid}/fitbit_heartrate_intraday.csv", pid=config["PIDS"]))
         files_to_compute.extend(expand("data/processed/features/{pid}/all_sensor_features.csv", pid=config["PIDS"]))
diff --git a/docs/datastreams/fitbitjson-mysql.md b/docs/datastreams/fitbitjson-mysql.md
index 4d654497..a4b4e1c2 100644
--- a/docs/datastreams/fitbitjson-mysql.md
+++ b/docs/datastreams/fitbitjson-mysql.md
@@ -60,6 +60,45 @@ If you want RAPIDS to process Fitbit sensor data using this stream, you will nee
                 |a748ee1a-1d0b-4ae9-9074-279a2b6ba524     |{"activities-heart":[{"dateTime":"2020-10-08","value":{"customHeartRateZones":[],"heartRateZones":[{"caloriesOut":1100.1120,"max":89,"min":30,"minutes":921,"name":"Out of Range"},{"caloriesOut":660.0012,"max":118,"min":82,"minutes":361,"name":"Fat Burn"},{"caloriesOut":23.7088,"max":142,"min":108,"minutes":3,"name":"Cardio"},{"caloriesOut":0,"max":221,"min":148,"minutes":0,"name":"Peak"}],"restingHeartRate":70}}],"activities-heart-intraday":{"dataset":[{"time":"00:00:00","value":77},{"time":"00:01:00","value":75},{"time":"00:02:00","value":73},...],"datasetInterval":1,"datasetType":"minute"}}
                 |a748ee1a-1d0b-4ae9-9074-279a2b6ba524     |{"activities-heart":[{"dateTime":"2020-10-09","value":{"customHeartRateZones":[],"heartRateZones":[{"caloriesOut":750.3615,"max":77,"min":30,"minutes":851,"name":"Out of Range"},{"caloriesOut":734.1516,"max":107,"min":77,"minutes":550,"name":"Fat Burn"},{"caloriesOut":131.8579,"max":130,"min":107,"minutes":29,"name":"Cardio"},{"caloriesOut":0,"max":220,"min":130,"minutes":0,"name":"Peak"}],"restingHeartRate":69}}],"activities-heart-intraday":{"dataset":[{"time":"00:00:00","value":90},{"time":"00:01:00","value":89},{"time":"00:02:00","value":88},...],"datasetInterval":1,"datasetType":"minute"}}
 
+??? info "FITBIT_HEARTRATE_INTRADAY"
+
+    **RAPIDS_COLUMN_MAPPINGS**
+
+    | RAPIDS column   | Stream column   |
+    |-----------------|-----------------|
+    | LOCAL_DATE_TIME       | FLAG_TO_MUTATE |
+    | DEVICE_ID       | device_id |
+    | HEARTRATE | FLAG_TO_MUTATE |
+    | HEARTRATE_ZONE | FLAG_TO_MUTATE |
+
+
+    **MUTATION**
+
+    - **COLUMN_MAPPINGS**
+
+        | Script column   | Stream column   |
+        |-----------------|-----------------|
+        | JSON_FITBIT_COLUMN      | fitbit_data      |
+    
+    - **SCRIPTS**
+    
+        ```bash
+        src/data/streams/mutations/fitbit/parse_heartrate_intraday_json.py
+        ```
+
+        !!! note
+            All columns except `DEVICE_ID` are parsed from `JSON_FITBIT_COLUMN`. `JSON_FITBIT_COLUMN` is a string column containing the JSON objects returned by Fitbit's API. See an example of the raw data RAPIDS expects for this data stream:
+
+
+            ??? "Example of the raw data RAPIDS expects for this data stream"
+
+                |device_id                                |fitbit_data                                               |
+                |---------------------------------------- |--------------------------------------------------------- |
+                |a748ee1a-1d0b-4ae9-9074-279a2b6ba524     |{"activities-heart":[{"dateTime":"2020-10-07","value":{"customHeartRateZones":[],"heartRateZones":[{"caloriesOut":1200.6102,"max":88,"min":31,"minutes":1058,"name":"Out of Range"},{"caloriesOut":760.3020,"max":120,"min":86,"minutes":366,"name":"Fat Burn"},{"caloriesOut":15.2048,"max":146,"min":120,"minutes":2,"name":"Cardio"},{"caloriesOut":0,"max":221,"min":148,"minutes":0,"name":"Peak"}],"restingHeartRate":72}}],"activities-heart-intraday":{"dataset":[{"time":"00:00:00","value":68},{"time":"00:01:00","value":67},{"time":"00:02:00","value":67},...],"datasetInterval":1,"datasetType":"minute"}}
+                |a748ee1a-1d0b-4ae9-9074-279a2b6ba524     |{"activities-heart":[{"dateTime":"2020-10-08","value":{"customHeartRateZones":[],"heartRateZones":[{"caloriesOut":1100.1120,"max":89,"min":30,"minutes":921,"name":"Out of Range"},{"caloriesOut":660.0012,"max":118,"min":82,"minutes":361,"name":"Fat Burn"},{"caloriesOut":23.7088,"max":142,"min":108,"minutes":3,"name":"Cardio"},{"caloriesOut":0,"max":221,"min":148,"minutes":0,"name":"Peak"}],"restingHeartRate":70}}],"activities-heart-intraday":{"dataset":[{"time":"00:00:00","value":77},{"time":"00:01:00","value":75},{"time":"00:02:00","value":73},...],"datasetInterval":1,"datasetType":"minute"}}
+                |a748ee1a-1d0b-4ae9-9074-279a2b6ba524     |{"activities-heart":[{"dateTime":"2020-10-09","value":{"customHeartRateZones":[],"heartRateZones":[{"caloriesOut":750.3615,"max":77,"min":30,"minutes":851,"name":"Out of Range"},{"caloriesOut":734.1516,"max":107,"min":77,"minutes":550,"name":"Fat Burn"},{"caloriesOut":131.8579,"max":130,"min":107,"minutes":29,"name":"Cardio"},{"caloriesOut":0,"max":220,"min":130,"minutes":0,"name":"Peak"}],"restingHeartRate":69}}],"activities-heart-intraday":{"dataset":[{"time":"00:00:00","value":90},{"time":"00:01:00","value":89},{"time":"00:02:00","value":88},...],"datasetInterval":1,"datasetType":"minute"}}
+
+
 ??? info "FITBIT_STEPS_SUMMARY"
 
     **RAPIDS_COLUMN_MAPPINGS**
diff --git a/docs/datastreams/mandatory-fitbit-format.md b/docs/datastreams/mandatory-fitbit-format.md
index ab86601f..6394cff2 100644
--- a/docs/datastreams/mandatory-fitbit-format.md
+++ b/docs/datastreams/mandatory-fitbit-format.md
@@ -15,6 +15,16 @@ This is a description of the format RAPIDS needs to process data for the followi
     | HEARTRATE_DAILY_CALORIESCARDIO |  Calories spent while heartrate was inside the cardio [zone](https://help.fitbit.com/articles/en_US/Help_article/1565.htm#) |
     | HEARTRATE_DAILY_CALORIESPEAK |  Calories spent while heartrate was inside the peak [zone](https://help.fitbit.com/articles/en_US/Help_article/1565.htm#) |
 
+??? info "FITBIT_HEARTRATE_INTRADAY"
+
+    | RAPIDS column   | Description   |
+    |-----------------|-----------------|
+    | TIMESTAMP       |  An UNIX timestamp (13 digits) when a row of data was logged |
+    | LOCAL_DATE_TIME       |  Date time string with format `yyyy-mm-dd hh:mm:ss` |
+    | DEVICE_ID       |  A string that uniquely identifies a device |
+    | HEARTRATE |  Intraday heartrate |
+    | HEARTRATE_ZONE |  Heartrate [zone](https://help.fitbit.com/articles/en_US/Help_article/1565.htm#) that HEARTRATE belongs to. It is based on the heartrate zone ranges of each device |
+
 ??? info "FITBIT_STEPS_SUMMARY"
 
     | RAPIDS column   | Description   |
diff --git a/rules/features.smk b/rules/features.smk
index 397d8ed1..0fad5212 100644
--- a/rules/features.smk
+++ b/rules/features.smk
@@ -558,7 +558,7 @@ rule fitbit_heartrate_summary_r_features:
 
 rule fitbit_heartrate_intraday_python_features:
     input:
-        sensor_data = "data/raw/{pid}/fitbit_heartrate_intraday_parsed_with_datetime.csv",
+        sensor_data = "data/raw/{pid}/fitbit_heartrate_intraday_with_datetime.csv",
         time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
     params:
         provider = lambda wildcards: config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"][wildcards.provider_key.upper()],
@@ -571,7 +571,7 @@ rule fitbit_heartrate_intraday_python_features:
 
 rule fitbit_heartrate_intraday_r_features:
     input:
-        sensor_data = "data/raw/{pid}/fitbit_heartrate_intraday_parsed_with_datetime.csv",
+        sensor_data = "data/raw/{pid}/fitbit_heartrate_intraday_with_datetime.csv",
         time_segments_labels = "data/interim/time_segments/{pid}_time_segments_labels.csv"
     params:
         provider = lambda wildcards: config["FITBIT_HEARTRATE_INTRADAY"]["PROVIDERS"][wildcards.provider_key.upper()],
diff --git a/src/data/streams/fitbitjson_mysql/format.yaml b/src/data/streams/fitbitjson_mysql/format.yaml
index 31ea979d..a9fd88da 100644
--- a/src/data/streams/fitbitjson_mysql/format.yaml
+++ b/src/data/streams/fitbitjson_mysql/format.yaml
@@ -14,6 +14,20 @@ FITBIT_HEARTRATE_SUMMARY:
     SCRIPTS: # List any python or r scripts that mutate your raw data
       - src/data/streams/mutations/fitbit/parse_heartrate_summary_json.py
 
+FITBIT_HEARTRATE_INTRADAY:
+  RAPIDS_COLUMN_MAPPINGS:
+    TIMESTAMP: FLAG_TO_MUTATE
+    DEVICE_ID: device_id
+    LOCAL_DATE_TIME: FLAG_TO_MUTATE
+    HEARTRATE: FLAG_TO_MUTATE
+    HEARTRATE_ZONE: FLAG_TO_MUTATE
+  MUTATION:
+    COLUMN_MAPPINGS:
+      JSON_FITBIT_COLUMN: fitbit_data # text column with JSON objects
+    SCRIPTS: # List any python or r scripts that mutate your raw data
+      - src/data/streams/mutations/fitbit/parse_heartrate_intraday_json.py
+
+
 FITBIT_STEPS_SUMMARY:
   RAPIDS_COLUMN_MAPPINGS:
     TIMESTAMP: FLAG_TO_MUTATE
diff --git a/src/data/streams/mutations/fitbit/parse_heartrate_intraday_json.py b/src/data/streams/mutations/fitbit/parse_heartrate_intraday_json.py
new file mode 100644
index 00000000..0ff3764d
--- /dev/null
+++ b/src/data/streams/mutations/fitbit/parse_heartrate_intraday_json.py
@@ -0,0 +1,83 @@
+import json
+import pandas as pd
+from datetime import datetime
+
+
+HR_INTRADAY_COLUMNS = ("device_id",
+                        "heartrate", 
+                        "heartrate_zone",
+                        "local_date_time",
+                        "timestamp")
+
+def parseHeartrateZones(heartrate_data):
+    # Get the range of heartrate zones: outofrange, fatburn, cardio, peak
+    # refer to: https://help.fitbit.com/articles/en_US/Help_article/1565
+
+    heartrate_fitbit_data = heartrate_data["activities-heart"][0]
+    # API Version X: not sure the exact version
+    if "heartRateZones" in heartrate_fitbit_data:
+        heartrate_zones = heartrate_fitbit_data["heartRateZones"]
+    # API VERSION Y: not sure the exact version
+    elif "value" in heartrate_fitbit_data:
+        heartrate_zones = heartrate_fitbit_data["value"]["heartRateZones"]
+    else:
+        raise ValueError("Heartrate zone are stored in an unknown format, this could mean Fitbit's heartrate API changed")
+    
+    heartrate_zones_range = {}
+    for hrzone in heartrate_zones:
+        heartrate_zones_range[hrzone["name"].lower().replace(" ", "")] = [hrzone["min"], hrzone["max"]]
+    return heartrate_zones_range
+
+
+def parseHeartrateIntradayData(records_intraday, dataset, device_id, curr_date, heartrate_zones_range):
+    for data in dataset:
+        d_time = datetime.strptime(data["time"], '%H:%M:%S').time()
+        d_datetime = datetime.combine(curr_date, d_time)
+        d_hr =  data["value"]
+
+        # Get heartrate zone by range: min <= heartrate < max
+        d_hrzone = None
+        for hrzone, hrrange in heartrate_zones_range.items():
+            if d_hr >= hrrange[0] and d_hr < hrrange[1]:
+                d_hrzone = hrzone
+                break
+
+        row_intraday = (device_id,
+                        d_hr, d_hrzone,
+                        d_datetime,
+                        0)
+
+        records_intraday.append(row_intraday)
+    return records_intraday
+
+
+
+def parseHeartrateData(heartrate_data):
+    if heartrate_data.empty:
+        return pd.DataFrame(columns=HR_INTRADAY_COLUMNS)
+
+    device_id = heartrate_data["device_id"].iloc[0]
+    records_intraday = []
+
+
+    # Parse JSON into individual records
+    for record in heartrate_data.json_fitbit_column:
+        record = json.loads(record)  # Parse text into JSON
+        if "activities-heart" in record:
+            heartrate_zones_range = parseHeartrateZones(record)
+            curr_date = datetime.strptime(record["activities-heart"][0]["dateTime"], "%Y-%m-%d")
+
+            if "activities-heart-intraday" in record:
+                dataset = record["activities-heart-intraday"]["dataset"]
+                records_intraday = parseHeartrateIntradayData(records_intraday, dataset, device_id, curr_date, heartrate_zones_range)
+    
+    parsed_data = pd.DataFrame(data=records_intraday, columns=HR_INTRADAY_COLUMNS)
+    return parsed_data
+    
+
+
+def main(json_raw, stream_parameters):
+    parsed_data = parseHeartrateData(json_raw)
+    parsed_data["timestamp"] = 0 # this column is added at readable_datetime.R because we neeed to take into account multiple timezones
+    parsed_data['local_date_time'] = parsed_data['local_date_time'].dt.strftime('%Y-%m-%d %H:%M:%S')
+    return(parsed_data)
diff --git a/src/data/streams/mutations/fitbit/parse_heartrate_summary_json.py b/src/data/streams/mutations/fitbit/parse_heartrate_summary_json.py
index daab3b5b..e6bac1c8 100644
--- a/src/data/streams/mutations/fitbit/parse_heartrate_summary_json.py
+++ b/src/data/streams/mutations/fitbit/parse_heartrate_summary_json.py
@@ -1,8 +1,6 @@
-import yaml, json, sys
+import json
 import pandas as pd
-import numpy as np
-from datetime import datetime, timezone
-from math import trunc
+from datetime import datetime
 
 
 HR_SUMMARY_COLUMNS = ("device_id",
diff --git a/src/data/streams/rapids_columns.yaml b/src/data/streams/rapids_columns.yaml
index 6aea61b3..7629b1d6 100644
--- a/src/data/streams/rapids_columns.yaml
+++ b/src/data/streams/rapids_columns.yaml
@@ -102,6 +102,13 @@ FITBIT_HEARTRATE_SUMMARY:
   - HEARTRATE_DAILY_CALORIESCARDIO
   - HEARTRATE_DAILY_CALORIESPEAK
 
+FITBIT_HEARTRATE_INTRADAY:
+  - TIMESTAMP
+  - DEVICE_ID
+  - LOCAL_DATE_TIME
+  - HEARTRATE
+  - HEARTRATE_ZONE
+
 FITBIT_STEPS_SUMMARY:
   - TIMESTAMP
   - DEVICE_ID