Measurement of Rural Firefighter Productivity & Workload Richard Parker 1, David Riley 2, Grant Pearce3 Stuart Anderson 3 1 Centre for Human Factors and Ergonomics, Scion, 49 Sala St, Rotorua, New Zealand,
[email protected] 2 Health & Safety Laboratory, Harpur Hill, Buxton, Derbyshire, SK17 9JN, Great Britain, 3 Ensis Bushfire Research Group, PO Box 29237, Christchurch, New Zealand Abstract Purpose To demonstrate a novel data collection ensemble comprised of video, heart rate and GPS to collect productivity and workload data from rural firefighters under actual operational conditions. Approach Firefighting is a hazardous and physically demanding task requiring a high level of fitness for productive front line operations. Firefighters often endure high levels of heat, are exposed to excessive smoke and dust, carry heavy equipment over often difficult terrain, and are expected to work at a high physiological load for extended periods. Our aim is to improve the health and safety of rural firefighters by determining, under New Zealand operational conditions, the physiological workload associated with rural firefighting tasks and to relate this to their actual fire suppression productivity. Results It is difficult to collect objective research data under actual firefighting conditions. To this end a novel and unobtrusive ensemble of data collection equipment comprising commercial off the shelf technology was developed. The equipment records the firefighters activities from helmet mounted video cameras, physiological workload by heart rate monitor and geographical location by GPS data logging. The three streams of data are then synchronised and analysed. Results have demonstrated that it is possible to quantify firefighter physical workload and fire suppression productivity under real fire conditions with little disruption to the firefighter. In addition, the data has potential to be used as a training resource. This data collection ensemble could be used in structural fire and rescue situations. Introduction This paper describes a method to collect field data in real fire conditions without disturbing the normal workflow of the firefighters. Unobtrusive data collection methods are required. The data collection methods must be relatively inexpensive, simple to administer and provide data in a form which is easily analysed. A study was required to measure physiological workload under real fire conditions. However, the direct observation of firefighters was difficult because of the danger involved in getting close, the speed of work and the disruptive effect of being watched. A data collection ensemble was developed which, when worn as a backpack enable the collection of heart rate, location from GPS and video. Many tasks in rural fire fighting are physically demanding (Budd, 2001; Gaskill, 2002; Heil, 2002) and result in high levels of fatigue. To date, much research work has been carried out by Australian and North American researchers to quantify workload and associated fatigue (Ruby, Scholler, & Sharkey, 2000, 2001; Ruby, Zderic, Burks, Tysk, & Sharkey, 1999). However, there are no published reports measuring New Zealand rural firefighter workload and fatigue. Data collection in this environment must not introduce new hazards. In addition the observer must be located a great distance away from the firefighters to remain safe. This results in a poor viewing position. In an attempt to gain a better view of the firefighters activities a miniature video camera was mounted on the firefighters helmet. Head mounted video cameras have been used to monitor the
visual attention of orienteers (Eccles, Walsh & Ingledew 2006) and the clinical reasoning of occupational therapists (Unsworth, 2001). An important feature of an observation study is to be able to collect the required information without changing the system under study. Such a study has a low reactivity. Reactivity (Drury, 2005) is the measure of how much the system is changed by the observer. This work will concern itself with observation studies developed to provide the lowest reactivity possible. An important consideration of an investigational technique is that it has face validity. The professional firefighting audience are critical subject experts and will more readily accept results obtained under real operational conditions. Method The system was refined on forest workers rather than firefighters because the researchers had ready access to forest workers. Opportunities for testing equipment on firefighters, at fires, were too infrequent. A number of different video cameras and recording devices were trialled in the field with forest workers under normal operational conditions. Problems were encountered with hard drive recording devices which were not resistant to the rapid movements of forest workers. Flash card recorders were much more resistant to the shocks resulting from rapid movement such as jumping or running. The ensemble described below was the product of many hours of trials in forest operations. The actions of the firefighter were recorded with a small (65 mm by 20 mm) colour PAL video camera (Xtremerecall 480 line Sony Ex-HAD) mounted on the firefighters helmet. The camera was powered by a separate 9 volt battery. Video was recorded to a Compact Flash (CF) card video recorder (Neuros Recorder 2) powered by an external Li-ion battery. The Neuros could record eight hours of 640 by 480 line PAL video onto a four gigabyte CF card at 25 frames / second. The video recorder and camera power supply were carried in a pack worn on the firefighters back (Figure 1). A microphone was attached a shoulder strap of the backpack at the level of the firefighters collar bone. Heart rate was detected and transmitted by a Polar chest strap to a data logger (GPSports SPI10) with an integrated GPS receiver and logger. Heart rate and GPS location were recorded every second for up to four hours. The reasons for the study were explained to the firefighter and his informed consent obtained. The two electrodes of the heart rate monitor chest strap were smeared in conductive paste and the strap fitted to the chest of the worker against his skin. The worker was then helped to put on the lightweight backpack containing the video and heart rate recorders and batteries. A start-up sequence for the monitoring devices was then initiated to assist synchronisation of the data streams. The heart rate monitor / GPS device was activated first because it required two minutes to acquire satellites and be ready for operation. While the heart rate monitor / GPS was activating the video camera operation was checked. The video recorder was activated on the firefighters backpack. The researcher then moved to the front of the worker, in view of the helmet mounted camera and initiated recording of the heart rate / GPS unit. Synchronisation could then be checked from the video record.
Video camera
Video recorder & camera battery
GPS
Heart rate monitor
Figure 1 - Firefighter wearing data collection ensemble. The firefighter was then free to commence his normal activities. The researcher retreated to a safe observation location. Recording continued for four hours when the battery of the video recorder was exhausted. The video record was automatically saved as a series on e hour MP4 files of one Gigabyte each. A coding scheme was set up in Noldus Observer XT using the elements described in Table 1. The elements were derived from discussion with experienced firefighters. Table 1 - Elements used to describe firefighter activities Element Walk Wait Talk Radio Hand tool use Hose handling Other
Description Walk Wait for a safe opportunity to complete or perform next task Talking to others Radio communication Digging, cutting Carrying hose, laying out hose Talk with researcher, eat, drink, other activities
The video file recorded from the helmet mounted video camera was imported into Observer XT. The corresponding heart rate data file from the GPSports monitor was then imported and synchronised with the video data. Coding of the video file into an event log file was performed using the Observer XT observation window (Figure 2). The play speed and direction of the video file could be controlled with the Observer XT interface enabling repeated views of an event to ensure accurate coding. The whole video file was coded and the codes saved in a synchronised event log. Most video files were one hour long.
Figure 2 – Observer XT observation window used to code fire activities A log file containing a sequential list of tasks and time of occurrence was generated from Observer XT. In Microsoft Excel the tasks were matched with the heart rate file and subsequently analysed in Minitab 13.1. The GPS record was overlaid on an aerial photo of the burn area showing the movements of the firefighter (Figure 3).
Observation area
Running up hill Mop-up area
Figure 3 – Location of firefighter during the study period derived from GPS data (scale on left side of photograph is in 50 m intervals)
Results & Discussion The playback controls of the Observer XT observation window were used to start, stop, rewind and play video at half speed to ensure coding of tasks was accurate. A simple summary of the data collected on one firefighter is presented in Table 2. Table 2 – Summary data of firefighter activity Measurement Total distance travelled Lowest heart rate Average heart rate Highest heart rate Fastest running Measurement duration
Task 5.2 km 71 bpm 129 bpm 185 bpm 11 km/hr 3 hr 27 min
Helmet-mounted v ideo and heart rate recording allowed unobtrusive monitoring of work, particularly in dangerous conditions where it would be impossible to observe safely and unobtrusively. The data collection ensemble was small and light weight and had acceptance from the firefighter. The firefighter reported that he often forgot that he had monitoring equipment on and continued to work in a normal way. The video camera was mounted on the firefighter’s helmet. This resulted in considerable movement of the video image and mounting the camera on the firefighter’s body is being investigated. Head mounted video suffers from frequent head movements, particularly in hazardous situations where situational awareness relies almost exclusively on vision and identifying the source of sound. Viewing the recorded video image with sound provided a cue of changes in task and made coding of tasks easier. For example running was characterised by the sound of heavy footfalls and loud breathing. Omodei & McLennan (1994) reported the sound of foot falls in head-mounted video from orienteers provided a strong cue to changes in direction. The video and associated heart rate were powerful and engaging images which provided an intense visual and auditory experience for those who have expert knowledge of firefighting. Experienced firefighters have suggested the images could be a valuable teaching aid because of their visual and auditory impact and face validity because they were recorded under real fire conditions. In their study of complex decision making during competitive orienteering Omodei and McLennan (1994) concluded that the ability to obtain visual information from the perspective of the participant allows for the provision of realistic stimulus environments to demonstrate correct procedures in training contexts. Information provide by the helmet-mounted video camera was limited to the area directly in front of the firefighter and below the horizontal. Unfortunately the limited field of view did not capture images of the surrounding area but did capture the field of view of the direction of the firefighters gaze. The firefighter often looked around for situational awareness while performing a manual task. Conclusion The data collection ensemble has proved useful in acquiring ‘real life’ data from a firefighter. The ensemble is being further developed into a more practical and robust second generation system. This work has been funded by the New Zealand Fire Service Commission Contestable Research Fund and the New Zealand Foundation for Research, Science and Technology.
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