Forestry is recognized as one of the most physically demanding professions. Walking in presents unique biomechanical challenges due to complex, irregular terrain, with several possible risks. This study investigated how human gait adapts across solid surfaces, forest trails, and natural forest environments. Fifteen healthy adult participants (average age 38.3; ten males and five females) completed 150 walking trials, with full-body motion captured via a 17 Inertial Measurement Unit (IMU) sensors (Xsens MVN Awinda system). The analysis focused on spatial and temporal gait parameters, including cadence, step length, foot strike pattern, and center of mass variability. Statistical methods (ANOVA and Kruskal–Wallis) revealed that surface type significantly influenced gait mechanics. On forest terrain, participants exhibited wider steps, reduced cadence, increased step and stride variability, and a substantial shift from heel-to-toe strikes. Gait adaptations reflect compensatory neuromuscular strategies to maintain body balance. The findings confirm that forestry terrain complexity compromises human gait stability and increases physical demands, supporting step variability and slip, trip, and fall risk. By identifying key biomechanical markers of instability, this study contributes to understanding human locomotion principles. Understanding these changes can help design safety measures for outdoor professions, particularly forestry.

Walking through forests poses unique challenges due to uneven terrain. There are several different Gait studies investigating conditions of human movement, in urban, laboratory, or other terrain simulations. This study examines how people adjust their gait when moving across solid surfaces, forest trails, and natural forest environments. Utilizing the digital Xsens MVN Awinda motion capture system using precise IMU units, data were collected from 15 participants across 150 walking trials. Gait analysis key findings revealed that gait parameters, including step length, cadence, and foot strike variability, were significantly influenced by terrain type. Uneven forestry surfaces resulted in increased step width, reduced cadence, and heightened center of mass variability, reflecting adaptive strategies to maintain stability and reduce fall risk. These biomechanical changes highlight the body's efforts to maintain balance in challenging terrains. The study findings offer valuable implications for improving mobility and reducing fall risks in forestry work activities. Understanding these changes can help design better safety measures for navigating complex outdoor environments.

Timber harvesting operations, including manual and motor-manual activities, require workers who are in good health to be able to work effectively. The aim of our paper was to introduce a simplified index methodology for workload assessment. Generally available wearable technology, namely Garmin, Biostrap, and Whoop devices, were used. The dependence of the heart rate (HR) on physical workload was examined to calculate the Heart Rate Index. The case study was performed with several variations of chainsaw devices cutting the poplar wood. It was proved that the use of a heavier work tool, MS 500i/90 cm 9.3 kg, contributes both to the creation of a non-ergonomic working position and to an increase in the energy required to perform work, which was represented by an increase in heart rate. With a lighter work tool and a shorter cutting blade, both a decrease in heart rate and a reduction in the working time performed in a non-ergonomic position were achieved. The results can be used in common practice for workers’ self-assessment to increase safety and health protection at work or work productivity, not only in forestry-related professions.

Forestry, nursery, and planting tasks involve repetitive trunk flexion, squatting, and kneeling, as well as manual handling, increasing musculoskeletal load, and the need for mobility-related safety measures. Passive exoskeletons could mitigate postural exposure and reduce the overall body workload. We conducted a preliminary study (n = 14) to test the feasibility of a protocol and estimated model- and task-specific trends during standardized simulated nursery activities in a laboratory setting. Participants simulated planting and seeding tasks (loads of 0.5–2 kg) and material handling and preparation tasks (loads of 5–15 kg) without an exoskeleton (No-EXO) and with three passive models (EXO 1–EXO 3). EXO 3 was excluded from the planting tasks for feasibility reasons. Whole-body kinematics were recorded using an IMU-based motion capture system and converted into time-based ergonomic exposure outcomes (OWAS and RULA). Physiological load was monitored via heart-rate (HR) measurements. Compared to the No-EXO condition, exoskeleton use shifted posture exposure towards lower-risk categories. The largest improvements were observed with EXO 2 and EXO 3 during material handling (OWAS: −18%/−20%; RULA action-level reduction: −25%/−39%) and with EXO 2 during planting/seeding (OWAS: −15%; RULA: −26%). HR_max did not increase across tasks or conditions and HR tended not to rise with higher workload when exoskeletons were used. Overall, the results suggest positive ergonomic and workload trends related to the model and tasks. Field validation on uneven terrain with full personal protective equipment and harness integration is needed to confirm usability and support and to define implementation requirements (fit, compatibility with PPE, and safe-use conditions).

Forestry operations expose workers to a high risk of health constraints, accidents, and injuries. We are trying to protect them and implement many effective countermeasures; nevertheless, the development of new forestry machines remains a long process, with limited safety and ergonomic feedback, usually provided only at a late stage in the design process. In this study, we propose a practical digital ergonomics workflow that combines inertial motion capture, standardized risk scoring, and digital human modelling to improve and shorten human-centered and safer design of forestry machinery. We validated the approach in a field pilot on a prototype milling–spraying device for standing trees. Two experienced operators performed a full work-cycle (carry → install → operate → dismantle → return), during which their whole-body kinematics were captured in real forest conditions. These were then evaluated using kinematic metrics, RULA, OWAS, and a heart-rate-based load index. Based on these ergonomical and risk findings, we translate motion-derived risk ‘hotspots’ into real redesign targets (grip/handle geometry, weight distribution, support elements, and control layout), outlining an updated forestry-specific DHM/HDT (digital human modeling; human digital twin) framework that explicitly incorporates terrain and environmental constraints to accelerate the iteration of safer prototypes. The updated digital modeling framework will be used in the design of the new, more complex machine—“Semi-autonomous system for optimizing degraded soils by deep injection”. This machine contains a much more complex and advanced structure, including a tractor with an attachment tool for specialized deep soil injection. We suppose that using motion capture data, human digital twins, and digital human models can effectively support designing and the development process to avoid human-related construction nonconformities of this complex machine even before the final machine prototype is produced for functional field testing.

The aim of the work was to carry out an ergonomic assessment of the workload when working with a chainsaw during motor-manual tree processing. Wearable technology was used, namely Garmin, Biostrap and Whoop devices, which are generally available. The dependence of the heart rate (HR) on physical workload was examined to calculate Heart Rate Index. The case study was done with one worker, three variations of chainsaw devices cutting the poplar wood. It was proved that the use of a heavier work tool, MS 500i /90 cm 9,3 kg, significantly contributes both to the creation of a non-physiological working position and to an increase in the energy required to perform work, which was represented by an increase in heart rate. With a lighter work tool and a shorter cutting blade, both a decrease in heart rate and a reduction in the working time were performed in a non-physiological position. The results can be used in common practice for workers´ self-assessment to increase safety and health protection at work or work productivity not only in motor-manual processing in forestry related professions.