SOCIODEMOGRAPHIC QUESTIONNAIRE

The sociodemographic questionnaire was used to define the social characteristics of the sample.

Information was collected on age, body mass, height, gender, education, time worked in banana processing, weekly workload and the dominant member.

2.3.2. Nordic QUESTIONNAIRE for MUSCULOSKELETAL symptoms

The Nordic questionnaire for musculoskeletal symptoms (Kuorinka et al., 1987), a reliable instrument that has been translated and vali- dated for the Brazilian population (Pinheiro et al., 2002), was applied to the three workers, and their responses were recorded by a researcher.

2.3.3. Discomfort AND USABILITY SCALE

This instrument is an adapted Borg scale (1982) consisting of three items answered in a ten- point Likert-type format (0 = None; 10 = Maximum). The evaluated items were: effort level

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required to carry out the task; discomfort level during the task and usability level during the task. The scales were designed as a series of 10 cm horizontal lines with the following attributes at each end: no effort and maximum effort; no discomfort and maximum discomfort; minimum usability and maximum usability.

Thus, after completing the task, which was removing bunches from the central stalk for a period of 5 min, the worker classified the level of effort, discomfort and usability felt while performing the activity by pointing it out on the scales.

2.3.4. DYNAMOMETRY

A SAEHAN® (SAEHAN Corporation, South Korea, Model DIGI II) manual grip dynamometer with a 90 kg maximum capacity and a 1 g scale was used to assess muscle strength. At the time of the tests, the individual was positioned as recommended by the American Society of Hand Therapists (Fess, 1992). The grip size was adjusted according to the anthropometric characteristics of each individual. Beginning with the dominant hand, four measurements were performed on each side. The first measurement was for familiarization with the equipment and was thus discarded. There was a 1 min rest between measurements to avoid muscle fatigue. The test instructions were standardized and verbal encouragement was given during each measurement. The verbal encouragement was kept at a constant rate to avoid any influence on the magnitude of muscle contraction (Taylor and Shechtman, 2000). The mean values of the three tests for each hand were used for data analysis.

2.3.5. Motion CAPTURE

Motion capture by inertial sensors was used to analyze the move- ment frequency, joint amplitudes and time taken to remove the bunches from the stalk. For data collection, an apparatus consisting of 17 inertial sensors attached to different parts of the body (Xsens MVN Biomech™, Enschede, the Netherlands) tracked the body segments, orientation, position, movement and center of mass. The system works in real time and captures data at a frequency of 120 Hz. The data was transmitted wirelessly to a computer loaded with software that allows the move- ments to be observed, recorded and analyzed based on graphs of joint angles and the speed and duration of the movements (Roetenberg et al., 2013). Each sensor contained three linear accelerometers and three orthogonal gyroscopes (Shippen and May 2016). This system

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is reliable and easy to use for data collection either inside or outside the labora- tory (Zhang et al., 2013).

The inertial sensors were positioned on the workers and calibrated according to manufacturer guidelines. The workers then performed the task in the usual manner for a period of 5 min, of which 4 min and 50 s were synchronized for myoelectric signal acquisition. Normally, five bunches of bananas can be removed in this amount of time. The data were analyzed in Xsens MVN Studio Pro software and exported to Microsoft Excel 2010 to calculate the means and standard deviations of the joint movement amplitudes and task execution time in order to identify musculoskeletal injury risks.

2.3.6. ELECTROMYOGRAPHY

Since EMG can demonstrate the physiological characteristics of muscles during work (Marras, 1990), it was used to verify muscle fa- tigue and the percentage of muscle fiber use during the bunch removal task. The right arm was the focus because it holds the tool that removes the bunches from the stalk. The RMS and MF were used to investigate fatigue. Muscle use, being related to the maximum voluntary isometric contraction (MVIC), was also verified.

Prior to EMG sensor placement, the skin was abraded with gauze and cleansed with 70%

isopropyl alcohol to reduce the signal inter- ference (Moraes et al., 2003; O'Sullivan and Schmitt, 2004).

Force and EMG signals were acquired using a Miotec 4-channel Miotool 400 system with Miograph 2.0 USB software, which trans- mitted the data to a computer. The acquisition rate was 2000 Hz per channel, with a 5 Hz high pass filter, a 500 Hz low pass filter and a 60 Hz notch filter.

To record the EMG signal, pairs of pre-gelled Ag/AgCl surface electrodes (Meditrace®) were adhered in a bipolar configuration, having a capture area of 1 cm in diameter and an inter- electrode distance of 2 cm. The electrodes (Fig. 2) were positioned over the upper trapezius (UT), brachial biceps (BB), extensor carpi radialis longus (ECRL) and flexor carpi radialis (FCR) of the right arm according to SENIAM standards (Hermens et al., 2002). The reference electrode was placed over the olecranon bone of the right arm. International Society of Electrophysiology and Kinesiology norms for EMG signal capture (Merletti, 2000) were strictly observed.

To obtain a MVIC for normalization of the EMG data, three 5-s tests were performed with 2 min rest between each attempt. To obtain a MVIC in the UT, resistance was applied to the

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elbow with the shoulder positioned in 90° of abduction with the neck side-bent to the same side and rotated to the opposite side, while resistance was simultaneously applied to the head (Ekstrom et al., 2005). MVIC of the right BB muscle was obtained with the arm at the side of the body and the elbow po- sitioned in 90° flexion in the supine position while manual resistance to elbow flexion was applied (Rainoldi et al., 1999). MVIC of the ECRL muscle was obtained with the arm at the side of the body, the elbow positioned in 90° flexion in the prone position while manual resistance to wrist extension was applied (Bandeira et al., 2009). MVIC of the FCR muscle was obtained with the arm at the side of the body, the elbow positioned in 90°

flexion in the supine position while manual resistance to wrist flexion was applied.

Figura 2: Electrode orientation.

Source: The authors, 2018

3. Results

3.1. Description of the bunch REMOVAL TASK

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The banana processing task consists of three steps: (i) supply (bringing a full stalk to the bunch removal area); (ii) removal (cutting and removing the bunches from the central stalk); and (iii) cleaning (placing the bunches in a tank of water). Since steps (i) and (iii) are shorter and more sporadic, only the removal step was analyzed in the present study. The tool used for this step is a common knife, a curved knife or even a spatula, although the curved knife (Fig. 14) is the most commonly used tool and the one the workers used in this study.

Figura 3: Demonstration of the task, postures and tools. Source: The authors, 2018

3.2. SOCIODEMOGRAPHIC AND OCCUPATIONAL CHARACTERISTICS of the PARTICIPANTS

The participants, who were all right-handed males, had a mean age of 56 ± 20.3 (W1: 34, W2:

74, W3: 60) years, a mean body mass of 72 ± 8.7 kg and a mean height was 1.69 ± 0.04 m.

Only one of the workers had graduated high school. The mean time they had been performing the above-described task was 5.3 ± 4.2 (W1: 2, W2: 10, W3: 4) years, with an average hourly load of 40.03 ± 4.73 h per week.

3.3. MUSCULOSKELETAL symptoms AND stress SCALE, discomfort AND USABILITY

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The most commonly reported pain in both the previous 12 months and the previous seven days was in the upper and lower back and in the thigh/hip region (33.33% and 33.33%, respectively).

The effort, discomfort and usability levels assessed in the bunch removal task are shown in Fig.

15.

As presented in Fig. 15, on the green-to-red (i.e., no-to-maximum) scales for effort and discomfort, the worker-reported levels were light for both variables. Likewise, on the red to- green usability scale, the level was also considered satisfactory.

Figura 4: Effort, discomfort and usability levels during the task. Source: The authors, 2018

3.4.DYNAMOMETRY

Due to being unavailable when the hand-grip strength test was administered, W2 did not perform it. W1's results were 67.9 ± 2.6 Kgf in the dominant hand and 62.3 ± 0.3 Kgf in the non-dominant hand, while W3's results were 41.7 ± 0.6 Kgf in the dominant hand and

46.1 ± 0.4 kg in the non-dominant hand. Thus, the dominant hand values ranged from 41.7 kg to 67.9 kg, with a mean of 54.8 kg, while the non-dominant values ranged from 46.1 Kgf to 62.3 Kgf, with a mean of 54.2.

3.5. INERTIAL sensor motion CAPTURE

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The analysis of movement frequency, joint amplitude and task completion time was performed with data obtained by inertial sensor motion capture in order to identify the risk of musculoskeletal injuries in the workers' upper limbs and cervical spine. Fig. 16 shows the mean joint angles and the standard deviations during the task. It should be pointed out that the three workers are right-handed, using the left hand to hold the main stalk and the right to remove the bunches with the cutting tool.

In the workers' right shoulder there was ≥60° abduction and flexion for a mean of 3.14% and 10.56% of the task, respectively. In the right wrist, there was ≥10° ulnar deviation for a mean time of 22.28%, while ≥15° radial deviation, flexion and extension occurred for a mean of 15.66%, 18.00% and 9.81% of the task, respectively. In the workers' C7-T1 joint, there was

≥20° flexion for a mean of 88.63% of the task, while in the L5-S1 joint, there was ≥1° degree left lateral flexion, ro- tation and forward flexion for a mean of 81.77%, 92.91% and 95.03% of the task, respectively.

Table 7 presents the mean time in seconds (with standard deviation) each worker took to remove one bunch of bananas. According to this data, in an 8-h shift the workers could remove up to 903 bunches. It should be emphasized that the other two steps in the task (supply and cleaning) are considered in this calculation as part of the standard de- viation.

WORKER TASK TIME STANDARD DEVIATION

T1 38,32 7,90

T2 31,39 9,57

T3 25,87 6,56

Média 31,86 9,07

Table 7: Time taken to remove one bunch of bananas.

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Figura 5: Mean joint angles and standard deviations during the task. Source: The authors, 2018.

3.6. Eletromiografia de superfície