# Heart Rate Index as a Measure of Physical Workload in Chainsaw Operations
## 4 Discussion  
To evaluate the performance of a work activity and the workload, we must consider not only the performance of the work itself but also the surrounding influences of the work environment, including the structure of the surrounding terrain, the work aids, the tools used, and the method and intensity of the activity performed. When performing combined work activities, as in our case, it is, therefore, necessary to consider the weight of the work tool and the method of deriving the force or lever, which is important for the performance of the work as part of the total load. Forestry work presents significant challenges for collecting reliable physiological data due to the intense physical demands and heavy equipment vibrations. These conditions can introduce motion artifacts and disrupt sensor readings, particularly for fashion wearable devices monitoring metrics like heart rate (HR) and heart rate variability (HRV). Ensuring data quality in such environments requires careful planning and mitigation strategies. From the ergonomic point of view, the primary goal of the activities carried out was to find the conditions to achieve the optimal well-being of the worker during the performance of work, while increasing efficiency protecting health and preventing risks at work. Forestry work shares many physiological stressors with other high-demand occupations. For example, studies on firefighters consistently report elevated heart (HR) rates and cardiovascular strain during peak activity periods, similar to the trends observed in forestry workers [42; 45; 46; 47]. Heavy machinery, such as chainsaws and harvesters, generates vibrations that may distort data collected by wearable sensors during wrist placement. Intense physical activities like lifting, climbing, and cutting further exacerbate this issue by disrupting sensor-skin contact and introducing noise into the signals. To address these challenges, wearable devices were chosen, incorporating accelerometers and gyroscopes to differentiate genuine physiological signals from motion-related interference. Sensor placement was another key factor. Devices were positioned on areas of the body less affected by movement or vibration, such as the forearm or upper arm for the Biostrap device. The worker was instructed to periodically check and adjust sensors during breaks to ensure consistent contact. Data collection was conducted under controlled environmental conditions where possible, reducing variability caused by heat or moisture. Quality control processes were critical for ensuring reliable data. Anomalies, such as sudden HR spikes inconsistent with physiological responses, were flagged and removed. Data from periods of excessive vibration or motion, identified via accelerometer inputs, were excluded from the analysis. When feasible, redundant measurements were taken using complementary methods to cross-verify results. While challenges remain, proactive measures such as good quality sensor selection, strategic placement, and rigorous quality checks minimize data disruptions. Future efforts should focus on developing ruggedized wearables and improved algorithms to further enhance data reliability in demanding forestry environments. This study demonstrates the potential for meaningful physiological insights despite environmental challenges. The future suggested topics for research could implement another element that might influence the performance of the worker such as parameters related to processed wood, relations between physical workload, working positions and body fatigue, the time needed for regeneration, measurement of muscles, idle mode, nutrition, and others. Wearable technology for physiological measurement in forestry has significant potential to improve worker safety and health. However, its deployment faces challenges related to the demanding conditions of forestry work. These challenges include environmental factors, data accuracy issues, power limitations, user comfort, and privacy concerns.