Abstract
This paper presents the results from a preliminary study where a wearable consumer electronic device was used to assess driver's state by capturing human physiological response in non-intrusive manner. Majority of state of the art studies have employed medical equipment drivers' state evaluation. Despite the potential gain in road safety this method of measuring physiology is unlikely to be accepted by private vehicle consumers due to its invasiveness, complexity, and high cost. This study was aiming to investigate possibility of employing a consumer grade wearable device to measure physiological parameters related to cognitive workload in real-time while driving i.e., drivers' heart rate. Furthermore, validity of captured heart activity metrics was analyzed to determine if wearable devices could be embedded into driving at its current technological state. The driving context was reproduced in desktop driving simulator, with 14 participants agreeing to take part in the study (μ = 28, σ = 8.5 years). Drivers were exposed to various road types, including pure Motorway, Rural, and Urban scenario modes. An accident was simulated in order to generate sudden cognitive arousal and capture participants' physiological response to the generated distress. It was found that a smartwatch is capable of reliable heart activity tracking in driving context. The results, supporting the relationship between cognitive workload level, generated by various complexity driving tasks, and Heart Rate Variability, were also presented.
| Original language | English |
|---|---|
| Title of host publication | 2016 IEEE Intelligent Vehicles Symposium, IV 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 55-60 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509018215 |
| DOIs | |
| Publication status | Published - 8 Aug 2016 |
| Externally published | Yes |
| Event | 2016 IEEE Intelligent Vehicles Symposium, IV 2016 - Gotenburg, Sweden Duration: 19 Jun 2016 → 22 Jun 2016 |
Publication series
| Name | IEEE Intelligent Vehicles Symposium, Proceedings |
|---|---|
| Volume | 2016-August |
Conference
| Conference | 2016 IEEE Intelligent Vehicles Symposium, IV 2016 |
|---|---|
| Country | Sweden |
| City | Gotenburg |
| Period | 19/06/16 → 22/06/16 |
Fingerprint
ASJC Scopus subject areas
- Computer Science Applications
- Automotive Engineering
- Modelling and Simulation
Cite this
JLR heart : Employing wearable technology in non-intrusive driver state monitoring. Preliminary study. / Melnicuk, Vadim; Birrell, Stewart; Konstantopoulos, Panos; Crundall, Elizabeth; Jennings, Paul.
2016 IEEE Intelligent Vehicles Symposium, IV 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 55-60 7535364 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2016-August).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding
}
TY - GEN
T1 - JLR heart
T2 - Employing wearable technology in non-intrusive driver state monitoring. Preliminary study
AU - Melnicuk, Vadim
AU - Birrell, Stewart
AU - Konstantopoulos, Panos
AU - Crundall, Elizabeth
AU - Jennings, Paul
PY - 2016/8/8
Y1 - 2016/8/8
N2 - This paper presents the results from a preliminary study where a wearable consumer electronic device was used to assess driver's state by capturing human physiological response in non-intrusive manner. Majority of state of the art studies have employed medical equipment drivers' state evaluation. Despite the potential gain in road safety this method of measuring physiology is unlikely to be accepted by private vehicle consumers due to its invasiveness, complexity, and high cost. This study was aiming to investigate possibility of employing a consumer grade wearable device to measure physiological parameters related to cognitive workload in real-time while driving i.e., drivers' heart rate. Furthermore, validity of captured heart activity metrics was analyzed to determine if wearable devices could be embedded into driving at its current technological state. The driving context was reproduced in desktop driving simulator, with 14 participants agreeing to take part in the study (μ = 28, σ = 8.5 years). Drivers were exposed to various road types, including pure Motorway, Rural, and Urban scenario modes. An accident was simulated in order to generate sudden cognitive arousal and capture participants' physiological response to the generated distress. It was found that a smartwatch is capable of reliable heart activity tracking in driving context. The results, supporting the relationship between cognitive workload level, generated by various complexity driving tasks, and Heart Rate Variability, were also presented.
AB - This paper presents the results from a preliminary study where a wearable consumer electronic device was used to assess driver's state by capturing human physiological response in non-intrusive manner. Majority of state of the art studies have employed medical equipment drivers' state evaluation. Despite the potential gain in road safety this method of measuring physiology is unlikely to be accepted by private vehicle consumers due to its invasiveness, complexity, and high cost. This study was aiming to investigate possibility of employing a consumer grade wearable device to measure physiological parameters related to cognitive workload in real-time while driving i.e., drivers' heart rate. Furthermore, validity of captured heart activity metrics was analyzed to determine if wearable devices could be embedded into driving at its current technological state. The driving context was reproduced in desktop driving simulator, with 14 participants agreeing to take part in the study (μ = 28, σ = 8.5 years). Drivers were exposed to various road types, including pure Motorway, Rural, and Urban scenario modes. An accident was simulated in order to generate sudden cognitive arousal and capture participants' physiological response to the generated distress. It was found that a smartwatch is capable of reliable heart activity tracking in driving context. The results, supporting the relationship between cognitive workload level, generated by various complexity driving tasks, and Heart Rate Variability, were also presented.
UR - http://www.scopus.com/inward/record.url?scp=84983338590&partnerID=8YFLogxK
U2 - 10.1109/IVS.2016.7535364
DO - 10.1109/IVS.2016.7535364
M3 - Conference proceeding
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 55
EP - 60
BT - 2016 IEEE Intelligent Vehicles Symposium, IV 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -