diff --git a/Snakefile b/Snakefile
index ae30484c..26076591 100644
--- a/Snakefile
+++ b/Snakefile
@@ -14,16 +14,10 @@ rule all:
                             sms_type = config["COM_SMS"]["SMS_TYPES"],
                             day_segment = config["COM_SMS"]["DAY_SEGMENTS"],
                             metric = config["COM_SMS"]["METRICS"]),
-        expand("data/processed/{pid}/com_call_{call_type}_{segment}_{metric}.csv",
+        expand("data/processed/{pid}/call_{call_type}_{segment}.csv",
                             pid=config["PIDS"], 
-                            call_type = config["COM_CALL"]["CALL_TYPE_MISSED"],
-                            segment = config["COM_CALL"]["DAY_SEGMENTS"],
-                            metric = config["COM_CALL"]["METRICS_MISSED"]),
-        expand("data/processed/{pid}/com_call_{call_type}_{segment}_{metric}.csv",
-                            pid=config["PIDS"], 
-                            call_type = config["COM_CALL"]["CALL_TYPE_TAKEN"],
-                            segment = config["COM_CALL"]["DAY_SEGMENTS"],
-                            metric = config["COM_CALL"]["METRICS_TAKEN"]),
+                            call_type=config["CALLS"]["TYPES"],
+                            segment = config["CALLS"]["DAY_SEGMENTS"]),
         expand("data/processed/{pid}/location_barnett.csv", pid=config["PIDS"]),
         expand("data/processed/{pid}/bluetooth_{segment}.csv",
                             pid=config["PIDS"], 
diff --git a/config.yaml b/config.yaml
index a1818aba..bdf4b451 100644
--- a/config.yaml
+++ b/config.yaml
@@ -30,12 +30,13 @@ COM_SMS:
 
 # Communication call features config
 # Separate configurations for missed and taken calls
-COM_CALL:
-  CALL_TYPE_MISSED : [missed]
-  CALL_TYPE_TAKEN : [incoming, outgoing]
+CALLS:
+  TYPES: [missed, incoming, outgoing]
+  METRICS:
+    missed:  [count, distinctcontacts]
+    incoming: [count, distinctcontacts, meanduration, sumduration, hubermduration, varqnduration, entropyduration]
+    outgoing: [count, distinctcontacts, meanduration, sumduration, hubermduration, varqnduration, entropyduration]
   DAY_SEGMENTS: *day_segments
-  METRICS_MISSED: [count, distinctcontacts]
-  METRICS_TAKEN: [count, distinctcontacts, meanduration, sumduration, hubermduration, varqnduration, entropyduration]
 
 PHONE_VALID_SENSED_DAYS:
   BIN_SIZE: 5 # (in minutes)
diff --git a/rules/features.snakefile b/rules/features.snakefile
index 125cee80..943b494b 100644
--- a/rules/features.snakefile
+++ b/rules/features.snakefile
@@ -10,15 +10,15 @@ rule communication_sms_metrics:
     script:
         "../src/features/communication_sms_metrics.R"
 
-rule communication_call_metrics:
+rule call_metrics:
     input: 
         "data/raw/{pid}/calls_with_datetime.csv"
     params:
         call_type = "{call_type}",
         day_segment = "{day_segment}",
-        metric = "{metric}"
+        metrics = lambda wildcards: config["CALLS"]["METRICS"][wildcards.call_type]
     output:
-        "data/processed/{pid}/com_call_{call_type}_{day_segment}_{metric}.csv"
+        "data/processed/{pid}/call_{call_type}_{day_segment}.csv"
     script:
         "../src/features/communication_call_metrics.R"
 
diff --git a/src/features/communication_call_metrics.R b/src/features/communication_call_metrics.R
index 5bc54bb5..3ca52704 100644
--- a/src/features/communication_call_metrics.R
+++ b/src/features/communication_call_metrics.R
@@ -4,27 +4,37 @@ library(dplyr)
 library(entropy)
 library(robustbase)
 
-calls <-  read.csv(snakemake@input[[1]])
-day_segment <- snakemake@params[["day_segment"]]
-metric <-  snakemake@params[["metric"]]
-type <- snakemake@params[["call_type"]]
-output_file <- snakemake@output[[1]]
+filter_by_day_segment <- function(data, day_segment) {
+  if(day_segment %in% c("morning", "afternoon", "evening", "night"))
+    data <- data %>% filter(local_day_segment == day_segment)
 
-metrics <- calls %>% filter(call_type == ifelse(type == "incoming", "1", ifelse(type == "outgoing", "2", "3")))
-
-if(day_segment == "daily"){
-  metrics <- metrics %>% group_by(local_date)
-} else {
-  metrics <- metrics %>% filter(day_segment == local_day_segment) %>% group_by(local_date)
+  return(data %>% group_by(local_date))
 }
 
-metrics <- switch(metric,
-       "count" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := n()),
-       "distinctcontacts" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := n_distinct(trace)),
-       "meanduration" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := mean(call_duration)),
-       "sumduration" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := sum(call_duration)),
-       "hubermduration" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := huberM(call_duration)$mu),
-       "varqnduration" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := Qn(call_duration)),
-       "entropyduration" = metrics %>% summarise(!!paste("com", "call", type, day_segment, metric, sep = "_") := entropy.MillerMadow(call_duration)))
+compute_call_feature <- function(calls, metric, day_segment){
+  calls <- calls %>% filter_by_day_segment(day_segment)
+  feature <- switch(metric,
+       "count" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := n()),
+       "distinctcontacts" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := n_distinct(trace)),
+       "meanduration" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := mean(call_duration)),
+       "sumduration" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := sum(call_duration)),
+       "hubermduration" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := huberM(call_duration)$mu),
+       "varqnduration" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := Qn(call_duration)),
+       "entropyduration" = calls %>% summarise(!!paste("call", type, day_segment, metric, sep = "_") := entropy.MillerMadow(call_duration)))
+  return(feature)
+}
 
-write.csv(na.omit(metrics), output_file, row.names = F)
+calls <-  read.csv(snakemake@input[[1]], stringsAsFactors = FALSE)
+day_segment <- snakemake@params[["day_segment"]]
+metrics <-  snakemake@params[["metrics"]]
+type <- snakemake@params[["call_type"]]
+features = data.frame(local_date = character(), stringsAsFactors = FALSE)
+
+calls <- calls %>% filter(call_type == ifelse(type == "incoming", "1", ifelse(type == "outgoing", "2", "3")))
+
+for(metric in metrics){
+  feature <- compute_call_feature(calls, metric, day_segment)
+  features <- merge(features, feature, by="local_date", all = TRUE)
+}
+
+write.csv(features, snakemake@output[[1]], row.names = FALSE)