diff --git a/config.yaml b/config.yaml
index 19b9629f..9325934c 100644
--- a/config.yaml
+++ b/config.yaml
@@ -68,7 +68,8 @@ RESAMPLE_FUSED_LOCATION:
   TIMEZONE: *timezone
 
 BARNETT_LOCATION:
-  LOCATIONS_TO_USE: ALL # ALL_EXCEPT_FUSED, RESAMPLE_FUSED
+  METRICS: ["hometime","disttravelled","rog","maxdiam","maxhomedist","siglocsvisited","avgflightlen","stdflightlen","avgflightdur","stdflightdur","probpause","siglocentropy","minsmissing","circdnrtn","wkenddayrtn"]
+  LOCATIONS_TO_USE: ALL # ALL, ALL_EXCEPT_FUSED OR RESAMPLE_FUSED
   ACCURACY_LIMIT: 51 # meters, drops location coordinates with an accuracy higher than this. This number means there's a 68% probability the true location is within this radius
   TIMEZONE: *timezone
 
diff --git a/rules/features.snakefile b/rules/features.snakefile
index c7218e85..b50ab43c 100644
--- a/rules/features.snakefile
+++ b/rules/features.snakefile
@@ -51,6 +51,7 @@ rule location_barnett_metrics:
         raw = "data/raw/{pid}/locations_raw.csv",
         fused = rules.resample_fused_location.output
     params:
+        metrics = config["BARNETT_LOCATION"]["METRICS"],
         locations_to_use = config["BARNETT_LOCATION"]["LOCATIONS_TO_USE"],
         accuracy_limit = config["BARNETT_LOCATION"]["ACCURACY_LIMIT"],
         timezone = config["BARNETT_LOCATION"]["TIMEZONE"]
diff --git a/src/features/location_barnett_metrics.R b/src/features/location_barnett_metrics.R
index bc643961..7ce0b9e5 100644
--- a/src/features/location_barnett_metrics.R
+++ b/src/features/location_barnett_metrics.R
@@ -2,7 +2,7 @@ source("packrat/init.R")
 
 library(dplyr)
 
-write_empty_file <- function(file_path){
+write_empty_file <- function(file_path, metrics_to_include){
   write.csv(data.frame(local_date= character(), 
                         hometime= numeric(), 
                         disttravelled= numeric(), 
@@ -19,7 +19,7 @@ write_empty_file <- function(file_path){
                         minsmissing= numeric(), 
                         circdnrtn= numeric(), 
                         wkenddayrtn= numeric()
-                      ), file_path, row.names = F)
+                      ) %>% select(metrics_to_include), file_path, row.names = F)
 }
 
 # Load Ian Barnett's code. Taken from https://scholar.harvard.edu/ibarnett/software/gpsmobility
@@ -29,6 +29,8 @@ sapply(file.sources,source,.GlobalEnv)
 locations_to_use <- snakemake@params[["locations_to_use"]]
 accuracy_limit <- snakemake@params[["accuracy_limit"]]
 timezone <- snakemake@params[["timezone"]]
+metrics_to_include <- intersect(unlist(snakemake@params["metrics"], use.names = F), 
+                                c("hometime","disttravelled","rog","maxdiam","maxhomedist","siglocsvisited","avgflightlen","stdflightlen","avgflightdur","stdflightdur","probpause","siglocentropy","minsmissing","circdnrtn","wkenddayrtn"))
 
 # By deafult we use all raw locations: fused without resampling and not fused (gps, network)
 location <- read.csv(snakemake@input[["raw"]], stringsAsFactors = F) %>%
@@ -47,16 +49,16 @@ if(locations_to_use == "ALL_EXCEPT_FUSED"){
 if (nrow(location) > 1){
     features <- MobilityFeatures(location, ACCURACY_LIM = accuracy_limit, tz = timezone)
     if(is.null(features)){
-      write_empty_file(snakemake@output[[1]])
+      write_empty_file(snakemake@output[[1]], metrics_to_include)
     } else{
       # Copy index (dates) as a column 
       outmatrix <- cbind(rownames(features$featavg), features$featavg)
       outmatrix <- as.data.frame(outmatrix)
       outmatrix[-1] <- lapply(lapply(outmatrix[-1], as.character), as.numeric)
       colnames(outmatrix)=c("local_date",tolower(colnames(features$featavg)))
-      write.csv(outmatrix,snakemake@output[[1]], row.names = F)
+      write.csv(outmatrix %>% select(metrics_to_include), snakemake@output[[1]], row.names = F)
     }
     
 } else {
-    write_empty_file(snakemake@output[[1]])    
+    write_empty_file(snakemake@output[[1]], metrics_to_include)    
 }
\ No newline at end of file