diff --git a/scripts/demo/demo_benchmark_app.sh b/scripts/demo/demo_benchmark_app.sh
index 25d1f94ae8e..a287c406d2b 100755
--- a/scripts/demo/demo_benchmark_app.sh
+++ b/scripts/demo/demo_benchmark_app.sh
@@ -33,8 +33,8 @@ case $key in
     shift
     ;;
     -sample-options)
-    sampleoptions="$2 $3 $4 $5 $6"
-    echo sample-options = "${sampleoptions}"
+    sampleoptions=("${@:2}")
+    echo sample-options = "${sampleoptions[*]}"
     shift
     ;;
     *)
@@ -44,8 +44,8 @@ esac
 shift
 done
 
-if ([ -z "$sampleoptions" ]); then
-    sampleoptions="-niter 1000"
+if [ -z "${sampleoptions[*]}" ]; then
+    sampleoptions=( -niter 1000 )
 fi
 
 target_precision="FP16"
@@ -71,12 +71,12 @@ else
 fi
 
 if ! . "$setupvars_path" ; then
-    printf "Unable to run ./setupvars.sh. Please check its presence. %s" "${run_again}"
+    echo -ne "Unable to run ./setupvars.sh. Please check its presence. ${run_again}"
     exit 1
 fi
 
 # Step 1. Download the Caffe model and the prototxt of the model
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "\n\nDownloading the Caffe model and the prototxt"
 
 cur_path=$PWD
@@ -143,7 +143,7 @@ elif [[ "$OSTYPE" == "darwin"* ]]; then
 fi
 
 if ! command -v $python_binary &>/dev/null; then
-    printf "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. %s" "${run_again}"
+    echo -ne "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. ${run_again}"
     exit 1
 fi
 
@@ -166,14 +166,14 @@ ir_dir="${irs_path}/${model_dir}/${target_precision}"
 
 if [ ! -e "$ir_dir" ]; then
     # Step 2. Configure Model Optimizer
-    printf "%s" "${dashes}"
+    echo -ne "${dashes}"
     printf "Install Model Optimizer dependencies\n\n"
     cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/install_prerequisites"
     . ./install_prerequisites.sh caffe
     cd "$cur_path"
 
     # Step 3. Convert a model with Model Optimizer
-    printf "%s" "${dashes}"
+    echo -ne "${dashes}"
     printf "Convert a model with Model Optimizer\n\n"
 
     mo_path="${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py"
@@ -182,11 +182,11 @@ if [ ! -e "$ir_dir" ]; then
     print_and_run "$python_binary" "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
 else
     printf "\n\nTarget folder %s already exists. Skipping IR generation  with Model Optimizer." "${ir_dir}"
-    printf "If you want to convert a model again, remove the entire %s folder. %s" "${ir_dir}" "${run_again}"
+    echo -ne "If you want to convert a model again, remove the entire ${ir_dir} folder. ${run_again}"
 fi
 
 # Step 4. Build samples
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Build Inference Engine samples\n\n"
 
 OS_PATH=$(uname -m)
@@ -211,15 +211,15 @@ cmake -DCMAKE_BUILD_TYPE=Release "$samples_path"
 make $NUM_THREADS benchmark_app
 
 # Step 5. Run samples
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Run Inference Engine benchmark app\n\n"
 
 cd "$binaries_dir"
 
 cp -f "$ROOT_DIR/${model_name}.labels" "${ir_dir}/"
 
-print_and_run ./benchmark_app -d "$target" -i "$target_image_path" -m "${ir_dir}/${model_name}.xml" -pc "${sampleoptions}"
+print_and_run ./benchmark_app -d "$target" -i "$target_image_path" -m "${ir_dir}/${model_name}.xml" -pc "${sampleoptions[@]}"
 
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 
 printf "Inference Engine benchmark app completed successfully.\n\n"
diff --git a/scripts/demo/demo_security_barrier_camera.sh b/scripts/demo/demo_security_barrier_camera.sh
index eaf6cd6784e..36e09cab7ba 100755
--- a/scripts/demo/demo_security_barrier_camera.sh
+++ b/scripts/demo/demo_security_barrier_camera.sh
@@ -33,8 +33,8 @@ case $key in
     shift
     ;;
     -sample-options)
-    sampleoptions="$2 $3 $4 $5 $6"
-    echo sample-options = "${sampleoptions}"
+    sampleoptions=("${@:2}")
+    echo sample-options = "${sampleoptions[*]}"
     shift
     ;;
     *)
@@ -112,7 +112,7 @@ elif [[ "$OSTYPE" == "darwin"* ]]; then
 fi
 
 if ! command -v $python_binary &>/dev/null; then
-    printf "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. %s" "${run_again}"
+    echo -ne "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. ${run_again}"
     exit 1
 fi
 
@@ -128,12 +128,12 @@ else
     printf "Error: setupvars.sh is not found\n"
 fi
 if ! . "$setupvars_path" ; then
-    printf "Unable to run ./setupvars.sh. Please check its presence. %s" "${run_again}"
+    echo -ne "Unable to run ./setupvars.sh. Please check its presence. ${run_again}"
     exit 1
 fi
 
 # Step 1. Downloading Intel models
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Downloading Intel models\n\n"
 
 
@@ -161,13 +161,13 @@ while read -r model_opt model_name; do
 done < "$ROOT_DIR/demo_security_barrier_camera.conf"
 
 # Step 2. Build samples
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Build Inference Engine demos\n\n"
 
 demos_path="${INTEL_OPENVINO_DIR}/deployment_tools/open_model_zoo/demos"
 
 if ! command -v cmake &>/dev/null; then
-    printf "\n\nCMAKE is not installed. It is required to build Inference Engine demos. Please install it. %s" "${run_again}"
+    echo -ne "\n\nCMAKE is not installed. It is required to build Inference Engine demos. Please install it. ${run_again}"
     exit 1
 fi
 
@@ -189,13 +189,13 @@ cmake -DCMAKE_BUILD_TYPE=Release "$demos_path"
 make $NUM_THREADS security_barrier_camera_demo
 
 # Step 3. Run samples
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Run Inference Engine security_barrier_camera demo\n\n"
 
 binaries_dir="${build_dir}/${OS_PATH}/Release"
 cd "$binaries_dir"
 
-print_and_run ./security_barrier_camera_demo -d "$target" -d_va "$target" -d_lpr "$target" -i "$target_image_path" "${model_args[@]}" "${sampleoptions}"
+print_and_run ./security_barrier_camera_demo -d "$target" -d_va "$target" -d_lpr "$target" -i "$target_image_path" "${model_args[@]}" "${sampleoptions[@]}"
 
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Demo completed successfully.\n\n"
diff --git a/scripts/demo/demo_squeezenet_download_convert_run.sh b/scripts/demo/demo_squeezenet_download_convert_run.sh
index 91a9055375b..24fc26c335c 100755
--- a/scripts/demo/demo_squeezenet_download_convert_run.sh
+++ b/scripts/demo/demo_squeezenet_download_convert_run.sh
@@ -33,8 +33,8 @@ case $key in
     shift
     ;;
     -sample-options)
-    sampleoptions="$2 $3 $4 $5 $6"
-    echo sample-options = "${sampleoptions}"
+    sampleoptions=("${@:2}")
+    echo sample-options = "${sampleoptions[*]}"
     shift
     ;;
     *)
@@ -67,12 +67,12 @@ else
 fi
 
 if ! . "$setupvars_path" ; then
-    printf "Unable to run ./setupvars.sh. Please check its presence. %s" "${run_again}"
+    echo -ne "Unable to run ./setupvars.sh. Please check its presence. ${run_again}"
     exit 1
 fi
 
 # Step 1. Download the Caffe model and the prototxt of the model
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "\n\nDownloading the Caffe model and the prototxt"
 
 cur_path=$PWD
@@ -139,7 +139,7 @@ elif [[ "$OSTYPE" == "darwin"* ]]; then
 fi
 
 if ! command -v $python_binary &>/dev/null; then
-    printf "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. %s" "${run_again}"
+    echo -ne "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. ${run_again}"
     exit 1
 fi
 
@@ -162,14 +162,14 @@ ir_dir="${irs_path}/${model_dir}/${target_precision}"
 
 if [ ! -e "$ir_dir" ]; then
     # Step 2. Configure Model Optimizer
-    printf "%s" "${dashes}"
+    echo -ne "${dashes}"
     printf "Install Model Optimizer dependencies\n\n"
     cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/install_prerequisites"
     . ./install_prerequisites.sh caffe
     cd "$cur_path"
 
     # Step 3. Convert a model with Model Optimizer
-    printf "%s" "${dashes}"
+    echo -ne "${dashes}"
     printf "Convert a model with Model Optimizer\n\n"
 
     mo_path="${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py"
@@ -178,11 +178,11 @@ if [ ! -e "$ir_dir" ]; then
     print_and_run "$python_binary" "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
 else
     printf "\n\nTarget folder %s already exists. Skipping IR generation  with Model Optimizer." "${ir_dir}"
-    printf "If you want to convert a model again, remove the entire %s folder. %s" "${ir_dir}" "${run_again}"
+    echo -ne "If you want to convert a model again, remove the entire ${ir_dir} folder. ${run_again}"
 fi
 
 # Step 4. Build samples
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Build Inference Engine samples\n\n"
 
 OS_PATH=$(uname -m)
@@ -207,14 +207,14 @@ cmake -DCMAKE_BUILD_TYPE=Release "$samples_path"
 make $NUM_THREADS classification_sample_async
 
 # Step 5. Run samples
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Run Inference Engine classification sample\n\n"
 
 cd "$binaries_dir"
 
 cp -f "$ROOT_DIR/${model_name}.labels" "${ir_dir}/"
 
-print_and_run ./classification_sample_async -d "$target" -i "$target_image_path" -m "${ir_dir}/${model_name}.xml" "${sampleoptions}"
+print_and_run ./classification_sample_async -d "$target" -i "$target_image_path" -m "${ir_dir}/${model_name}.xml" "${sampleoptions[@]}"
 
-printf "%s" "${dashes}"
+echo -ne "${dashes}"
 printf "Demo completed successfully.\n\n"