diff --git a/Snakefile b/Snakefile
index dc023282..e95d14ab 100644
--- a/Snakefile
+++ b/Snakefile
@@ -104,10 +104,12 @@ for provider in config["LIGHT"]["PROVIDERS"].keys():
         files_to_compute.extend(expand("data/interim/{pid}/{sensor_key}_features/{sensor_key}_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["LIGHT"]["PROVIDERS"][provider]["SRC_LANGUAGE"], provider_key=provider, sensor_key="LIGHT".lower()))
         files_to_compute.extend(expand("data/processed/features/{pid}/{sensor_key}.csv", pid=config["PIDS"], sensor_key="LIGHT".lower()))
 
-if config["ACCELEROMETER"]["COMPUTE"]:
-    files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
-    files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
-    files_to_compute.extend(expand("data/processed/{pid}/accelerometer_{day_segment}.csv", pid = config["PIDS"], day_segment = config["ACCELEROMETER"]["DAY_SEGMENTS"]))
+for provider in config["ACCELEROMETER"]["PROVIDERS"].keys():
+    if config["ACCELEROMETER"]["PROVIDERS"][provider]["COMPUTE"]:
+        files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
+        files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["ACCELEROMETER"]["DB_TABLE"]))
+        files_to_compute.extend(expand("data/interim/{pid}/{sensor_key}_features/{sensor_key}_{language}_{provider_key}.csv", pid=config["PIDS"], language=config["ACCELEROMETER"]["PROVIDERS"][provider]["SRC_LANGUAGE"], provider_key=provider, sensor_key="ACCELEROMETER".lower()))
+        files_to_compute.extend(expand("data/processed/features/{pid}/{sensor_key}.csv", pid=config["PIDS"], sensor_key="ACCELEROMETER".lower()))
 
 for provider in config["APPLICATIONS_FOREGROUND"]["PROVIDERS"].keys():
     if config["APPLICATIONS_FOREGROUND"]["PROVIDERS"][provider]["COMPUTE"]:
diff --git a/config.yaml b/config.yaml
index a852c126..62f89236 100644
--- a/config.yaml
+++ b/config.yaml
@@ -158,16 +158,14 @@ LIGHT:
       SRC_FOLDER: "rapids" # inside src/features/light
       SRC_LANGUAGE: "python"
 
-
 ACCELEROMETER:
-  COMPUTE: False
   DB_TABLE: accelerometer
-  DAY_SEGMENTS: *day_segments
-  FEATURES:
-    MAGNITUDE: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
-    EXERTIONAL_ACTIVITY_EPISODE: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
-    NONEXERTIONAL_ACTIVITY_EPISODE: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
-    VALID_SENSED_MINUTES: False
+  PROVIDERS:
+    RAPIDS:
+      COMPUTE: False
+      FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
+      SRC_FOLDER: "rapids" # inside src/features/accelerometer
+      SRC_LANGUAGE: "python"
 
 APPLICATIONS_FOREGROUND:
   DB_TABLE: applications_foreground
diff --git a/rules/features.smk b/rules/features.smk
index 2e8424ad..7945d62d 100644
--- a/rules/features.smk
+++ b/rules/features.smk
@@ -28,19 +28,31 @@ rule resample_episodes_with_datetime:
     script:
         "../src/data/readable_datetime.R"
 
-rule accelerometer_features:
+rule accelerometer_r_features:
     input:
-        expand("data/raw/{{pid}}/{sensor}_with_datetime.csv", sensor=config["ACCELEROMETER"]["DB_TABLE"]),
+        sensor_data = expand("data/raw/{{pid}}/{sensor}_with_datetime.csv", sensor=config["ACCELEROMETER"]["DB_TABLE"])[0],
+        day_segments_labels = "data/interim/day_segments/{pid}_day_segments_labels.csv"
     params:
-        day_segment = "{day_segment}",
-        magnitude = config["ACCELEROMETER"]["FEATURES"]["MAGNITUDE"],
-        exertional_activity_episode = config["ACCELEROMETER"]["FEATURES"]["EXERTIONAL_ACTIVITY_EPISODE"],
-        nonexertional_activity_episode = config["ACCELEROMETER"]["FEATURES"]["NONEXERTIONAL_ACTIVITY_EPISODE"],
-        valid_sensed_minutes = config["ACCELEROMETER"]["FEATURES"]["VALID_SENSED_MINUTES"],
+        provider = lambda wildcards: config["ACCELEROMETER"]["PROVIDERS"][wildcards.provider_key],
+        provider_key = "{provider_key}",
+        sensor_key = "accelerometer"
     output:
-        "data/processed/{pid}/accelerometer_{day_segment}.csv"
+        "data/interim/{pid}/accelerometer_features/accelerometer_r_{provider_key}.csv"
     script:
-        "../src/features/accelerometer_features.py"
+        "../src/features/entry.R"
+
+rule accelerometer_python_features:
+    input:
+        sensor_data = expand("data/raw/{{pid}}/{sensor}_with_datetime.csv", sensor=config["ACCELEROMETER"]["DB_TABLE"])[0],
+        day_segments_labels = "data/interim/day_segments/{pid}_day_segments_labels.csv"
+    params:
+        provider = lambda wildcards: config["ACCELEROMETER"]["PROVIDERS"][wildcards.provider_key],
+        provider_key = "{provider_key}",
+        sensor_key = "accelerometer"
+    output:
+        "data/interim/{pid}/accelerometer_features/accelerometer_python_{provider_key}.csv"
+    script:
+        "../src/features/entry.py"
 
 rule activity_recognition_episodes:
     input:
diff --git a/src/features/accelerometer/rapids/main.py b/src/features/accelerometer/rapids/main.py
new file mode 100644
index 00000000..09920343
--- /dev/null
+++ b/src/features/accelerometer/rapids/main.py
@@ -0,0 +1,36 @@
+import pandas as pd
+import numpy as np
+
+def rapids_features(sensor_data_files, day_segment, provider, filter_data_by_segment, *args, **kwargs):
+
+    acc_data = pd.read_csv(sensor_data_files["sensor_data"])
+    requested_features = provider["FEATURES"]
+    # name of the features this function can compute
+    base_features_names = ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
+    # the subset of requested features this function can compute
+    features_to_compute = list(set(requested_features) & set(base_features_names))
+
+    acc_features = pd.DataFrame(columns=["local_segment"] + ["acc_rapids_" + x for x in features_to_compute])
+    if not acc_data.empty:
+        acc_data = filter_data_by_segment(acc_data, day_segment)
+        
+        if not acc_data.empty:
+            acc_features = pd.DataFrame()
+            # get magnitude related features: magnitude = sqrt(x^2+y^2+z^2)
+            magnitude = acc_data.apply(lambda row: np.sqrt(row["double_values_0"] ** 2 + row["double_values_1"] ** 2 + row["double_values_2"] ** 2), axis=1)
+            acc_data = acc_data.assign(magnitude = magnitude.values)
+            
+            if "maxmagnitude" in features_to_compute:
+                acc_features["acc_rapids_maxmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].max()
+            if "minmagnitude" in features_to_compute:
+                acc_features["acc_rapids_minmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].min()
+            if "avgmagnitude" in features_to_compute:
+                acc_features["acc_rapids_avgmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].mean()
+            if "medianmagnitude" in features_to_compute:
+                acc_features["acc_rapids_medianmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].median()
+            if "stdmagnitude" in features_to_compute:
+                acc_features["acc_rapids_stdmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].std()
+            
+            acc_features = acc_features.reset_index()
+
+    return acc_features