# Explainable AI-Enhanced Human Activity Recognition for Human-Robot Collaboration in Agriculture
## 2 Materials and Methods
### Data Acquisition  
The field experimental sessions, described in detail in [27], took place on a farm located in central Greece. In short, a total of 20 participants (10 males, 10 females) voluntarily took part in the experiments. The selection of participants with diverse characteristics, including variations in gender, age, weight, and height, was deliberate, ensuring that the data collected represented a broad spectrum of variability. The participants had an average age of 30.13 years (standard deviation (SD) \(\approx\) 4.13 years), an average weight of 70.2 kg (SD \(\approx\) 16.1 kg), and an average height of 1.71 m (SD \(\approx\) 0.10 m). Eligibility for the study required all individuals to be free from any musculoskeletal injuries or surgical procedures within the past year that could impair their physical performance. Before the experiments began, all participants gave their informed consent, with the study protocol receiving prior approval from the Institutional Ethical Committee. Each participant was also required to engage in a five-minute warm-up before commencing the testing procedures to help prevent injuries [36; 37]. The participants were instructed to perform the following sequence of actions: (1) stand still until the start signal; (2) walk 3.5 m in a straight line; (3) lean down to pick up a crate; (4) lift the crate to a standing posture; (5) carry the crate while walking back 3.5 m; and (6) position the crate on the available UGV. The individuals were required to carry either an empty crate weighing 1.5 kg or a crate loaded with weight plates, totaling one-fifth of their body mass [38; 39]. Weight adjustments were made using 1 kg and 2.5 kg plates for precise calibration. Each participant completed both scenarios (one with an empty crate and one with a loaded crate) three times each in a random sequence, allowing them to set their own pace throughout the process. The experimental setup utilized a commonly used UGV (Thorvald, SAGA Robotics SA, Oslo, Norway), depicted in Figure 2, for agricultural field applications, which featured a crate deposit height of 80 cm. For data collection, five IMUs (Blue Trident, Vicon, Nexus, Oxford, UK), normally used in similar studies [40; 41; 42], were employed. Each IMU contained a tri-axial accelerometer (measured magnitude: acceleration; range/units: \(\pm\) 16 g; sensitivity: 16-bit), gyroscope (measured magnitude: angular velocity; range/units: \(\pm\)2000 \({}^{\circ}\)/s; sensitivity: 16-bit), and magnetometer (measured magnitude: direction/position; range/units: \(\pm\) 4900 \(\mu\)T; sensitiv  
Figure 2: A visual representation of the wearable sensors’ placement on the human body along with the available crate and unmanned ground vehicle (UGV) used in the experimental sessions. ity: 16-bit), allowing for detailed motion tracking along three axes [43]. The 50 Hz sampling rate ensured adequate temporal resolution for capturing the dynamics of the movements performed within the scope of this study [26; 39]. The data collected by the five IMUs (in CSV format) were stored directly on each sensor, with each file containing information about the specific body location. The sensors were interfaced with a data acquisition system connected to a computer for offline analysis. Capture.U software 1.4.1 [44] was used to synchronize the IMUs, while its installation on an Apple iPad mini (64 GB) facilitated the simultaneous recording of video during the experiments. This feature provided a clear visual cue, enabling the manual segmentation of the activity data into distinct epochs and the precise localization of temporal events marking transitions between activities. The activities to be recognized were as follows:  
1. Standing still (Class 0): the participant remains stationary without movement, awaiting the start signal to initiate the task;
2. Walking without a crate (Class 1): this activity begins when one foot makes contact with the ground to support the participant's body weight, while the other foot prepares to lift off for the subsequent step;
3.