Influence of handle shape and size to reduce the hand-arm vibration discomfort

Abstract

BACKGROUND:

Non-automated tool handles transmit a large magnitude of vibration to operators’ hands, causing discomfort and pain. Therefore, the need for a better handle design is a matter of prime concern to overcome musculoskeletal disorders such as hand-arm vibration syndrome.

OBJECTIVE:

This study aimed to examine the influence of handle shapes in reducing the transmission of hand-arm vibration.

METHODS:

Seven different handles were designed and fabricated using 3D printing technology at the SSN College of Engineering, with consideration for the anatomical shape of the hand. The frequency-weighted Root Mean Square (RMS) values of the vibration levels transmitted were recorded at the wrist of twelve subjects, unaffected by musculoskeletal disorders. Subjective ratings of vibration and comfort perception were measured using the Borg Scale of Perceived Exertion.

RESULTS:

The total vibration value (a_hv) of each of the six novel prototype handles (B-G) was compared to that of the reference handle denoted handle-A. The vibration reductions for handles B to G respectively were 0.542 m/s² (14.59%), 0.481 m/s² (12.95%), 0.351 m/s² (9.45%), 0.270 m/s² (7.27%), 0.407 m/s² (10.96%) and 0.192 m/s² (5.17%).

CONCLUSIONS:

A significant level of vibration reduction was achieved by the prototype handles. Qualitative feedback from the study subjects suggests that they were not aware of the levels of vibration being transmitted to the hand with each handle.

Keywords

Hand-arm vibration syndrome musculoskeletal disorders hand-transmitted vibration handle diameter vibration reduction occupational ergonomics

1 Introduction

Hand-operated and semi-automated tools are widely used in manufacturing industries. The hand-arm vibration transmitted from vibrating tool handles and equipment can cause workers to experience discomfort and pain in the upper extremities [1]. Continuous, long-term occupational exposure can cause workers to develop hand-arm vibration syndrome (HAVS) and cumulative trauma disorders (CTDs) associated with neurological, muscular, circulatory, bone and joint consequences [2 –4]. Vibration injury is a multidimensional problem that can affect every aspect of an individual’s life (e.g. vibration white finger, cumulative trauma disorders, etc.) [5]. The European Union (2005) has characterized the exposure limit value of 5.0 m/s² and exposure action value of 2.5 m/s² for 8 hour working days.

Poor tool handle design can cause discomfort to workers’ and result in early fatigue. Over time, this may contribute to the development of physiological and physical disorders [4]. Improved handle design is essential to prevent unnecessarily grip force, improper hand posture and fatigue. A maximum torque condition, the diameters of the handles 37–44 mm and 41–48 mm (23.3% of the user’s hand length) have been recommended for females and males respectively [6]. Shape [8], handle size [9], texture [10] and surface type [11] are some factors to be considered for designing improved tool handles. Handle size to maximize grip strength and prevent stress on the tendons [12]. In order to reduce the discomfort and pain associated with hand tool use, optimum handle size and shape should be taken into consideration for tool design [13]. An accurately designed handle can improve workers’ safety, comfort and performance during work whilst preventing the development of disorders [7]. Thus, designing vibrating handles that can reduce vibration transmission is of interest.

Ergonomic analysis should be included in the design phase because the main function of the product and the form of the product are firmly interconnected [15, 16]. Improved performance and reduced user discomfort were found in studies where ergonomic principles were considered at the industrial product phase [14]. Tool-handle based Digital Human Hand Model (DHHM) is a production technique that accounts for the optimal-power grasp posture, in order to mitigate the risk of cumulative trauma disorders (CTD) and improve subjective comfort-rating [17].

From a biomechanic perspective, the hand is very complicated and flexible in structure [18]. Therefore, it is important to understand the hand-arm response to vibration during hand-tool design. The level of vibration transmitted from a hand-tool to the operator’s arm is influenced by the operator’s posture, grip force, push force and the bio-dynamic responses of their fingers, hands and arms [19]. The bio-dynamic response of the fingers to hand-arm vibration differs from that dispersed to the palm of the hand [18]. Several researchers have analyzed vibration transmitted along the dominant direction (Z_h-direction the magnitude of vibration level found maximum) [20 –23], whereas experimental investigations have been conducted to evaluate the magnitude of vibration total values (a_hv). Duration of vibration exposure has also been considered by the researchers estimating the vibration total values [24 –26].

The acceleration peaks generated by vibrating hand-tools are a contributing factor to the harmful effects of vibration exposure. The vibration transmitted to the upper extremities can be reduced with the proper utilization of anti-vibration gloves [27 –29] or isolators (vibration damping isolators inserted at the handle-machine interface) [30, 31]. The use of an air-bladder glove or foam-padded glove can significantly attenuate the hand-arm transmitted vibration, compared to the individual’s bare hands [32]. In a study of six anti-vibration interventions (five glove types and a visco-elastic tool wrap), sheet assembly workers’ that used the glove or wrap perceived a reduction in vibration transmission compared to that perceived by workers working bare-handed [33]. However, anti-vibration gloves have been found to be less effective for people with sizable hands (i.e. hand size in the 90th to 95th percentiles) exposed to vibration in the frequency range of 50–100 Hz [18].

Another study, examined the effectiveness of vibration isolators in the engine and the handle of a tractor. Frequency-weighted Root Mean Square (RMS) acceleration was reduced by 29.8% and the subjective rating of arm soreness was reduced by 32%–61% when the vibration isolators were used [31]. While anti-vibration gloves and isolators can reduce vibration transmission and prevent hand-arm vibration syndrome, their efficacies are limited by the magnitude of vibration and frequency [34 –37].

According to the hierarchy of controls, controlling vibration at the source by improving tool handle design is optimal. The majority of the literature focuses on the cylindrical and elliptical shape of tool handles. However, the anatomical shape of the hand has not been considered in tool handle designs. The objectives of the present study are to (1) develop ergonomic tool handles by considering the anatomical shape of the hand; (2) quantify hand-arm vibration transmission from the prototype handles; and (3) examine users’ perception of vibration and comfort with the prototype.

2 Material and methods

2.1 Recruitment

Twelve males, 21 to 40 years of age, from the SSN College of Engineering in Chennai, India, volunteered to participate in this study. All subjects were right-hand dominant, unaffected by musculoskeletal conditions and had no remarkable medical history. Each subject was provided a brief description of the study procedure. Table 1 shows anthropometric measurements of the study participants.

Table 1
Anthropometric characteristics of study participants

Characteristics Mean Standard deviation Range

Age (years) 31 6.78 22–40

Height (cm) 166 4.92 159–172

Weight (kg) 73 5.89 65–81

Middle finger length (mm) 190 4.86 180–194

Thumb finger length (mm) 112 4.66 106–120

Grip diameter^* (mm) 53 3.65 48–55

Characteristics	Mean	Standard deviation	Range
Age (years)	31	6.78	22–40
Height (cm)	166	4.92	159–172
Weight (kg)	73	5.89	65–81
Middle finger length (mm)	190	4.86	180–194
Thumb finger length (mm)	112	4.66	106–120
Grip diameter^* (mm)	53	3.65	48–55

^*The diameter grip (D_grip) is the maximum diameter that can be grasped by a subject when the middle finger and the thumb finger are in contact.

2.2 Reference handle diameter

The mathematical relationship between anthropometric parameters such as grip force, handle diameter, hand size and contact area were investigated [38]. Optimal tool handle diameter was achieved when the middle fingertip and the thumb fingertip aligned parallel. The reference handle diameter was calculated as 44 mm on the basis of the anthropometric grip diameter (D_grip) using Equation (1).

$D_{opt} = \frac{D_{grip} \times \frac{π (L_{F, 2} + L_{T})}{2}}{π}$ (1) $L_{F, 2} = 0.14 L_{middle}$ $L_{T} = 0.26 L_{thumb}$ where, D_grip denotes grip diameter, L_middle denotes wrist to middle fingertip length, L_thumb denotes wrist to thumb fingertip length, L_F, 2 denotes the middle fingertip length and L_T denotes thumb tip length.

2.3 Mold preparation and 3D laser scanning

Considering the calculated optimal diameter of 44 mm and length of 120 mm, six different shaped molds were designed using modeling software SOLIDWORKS 2016^® (Fig. 1). The design patterns were made from polypropylene material and manufactured by the Computer Numerical Control (CNC) milling machine. Alginate impression material was used to obtain the shape of the molds. One subject was asked to hold the alginate impression material in order to examine the anatomical shape of their hand while the middle of the middle fingertip and thumb fingertip lay along a line parallel to the longitudinal axis (Fig. 2). Three Dimensional (3D) laser scanning was used to produce 3D models for each of the six alginate models with hand impressions (Fig. 3).

Fig.1

Top view of six different shape molds for handles B–G.

Fig.2

Alginate impression material used to consider the anatomical shape of the hand.

Fig.3

3D scanned image of the alginate impression model in STereoLithography (STL) format.

2.4 Segmentation and 3D construction

The images obtained from the 3D laser scanner were imported to the modeling software SOLIDWORKS 2016^® for further segmentation and construction. Feature recognition technique was used to identify small inclusions, segmentation errors, holes and ribs. Surface smoothening was performed using 3D reconstruction technique (Fig. 4).

Fig.4

Smooth 3D representation of handle in STereoLithography (STL) format.

2.5 Tool handles prototyping

Tool handle prototypes were made out of white Acrylonitrile Butadiene Styrene (ABS) plastic with a smooth surface finish, using a 3D printer (Fig. 5). A detailed description of the prototype handles is provided in Table 2. A cylinder-shaped handle (the reference handle) was manufactured by the same process but without consideration of hand impression (diameter of 44 mm and length of 120 mm). Vibration transmission and comfort were compared between this handle and the prototype handles.

Fig.5

Different types of prototype handle attached with the fixture.

Table 2

Types of handle designs

Handle name	Shape	Description
Handle A	Cylindrical	Without considering anatomical shape of hand
Handle B	Cylindrical	Considering anatomical shape of hand
Handle C	Elliptical	Considering anatomical shape of hand
Handle D	Hexagonal	Considering anatomical shape of hand
Handle E	Pentagonal	Considering anatomical shape of hand
Handle F	Semi-triangular	Considering anatomical shape of hand
Handle G	Triangular	Considering anatomical shape of hand

2.6 Hand-arm vibration measurements

Hand-arm vibration was measured using a tri-axial accelerometer (Kistler, 8763), electrodynamic exciter (Dongling, ESD045) and data acquisition system (DAQ with dynamic analyzer, 9234) through a NI USB-9234 card to Lenovo laptop (Core 2 duo Processor based). Vibration levels were analyzed in all directions (X_{h_}, Y_{h_} and Z_{h_}) with a sampling rate of 2048 frames per second using DEWESOFT software (Version X2). The coordinate axes used were in accordance with ISO 5349-1086. The NIOSH (1989) [40] recommendation is that the weight of the accelerometer be less than 5 g and the total weight of the accelerometer and adapter be less than 20 g [39, 40]. The accelerometer used in the present study weighed 2.4 g and was attached to subjects’ wrists using a light-weight strip in compliance with ISO 5349-2 (Fig. 6). Further details of the experimental setup and measurement process are, re-described in Fig. 6.

Fig.6

Experimental setup for vibration measurements at the wrist of the participant.

2.7 Experimental procedure

Vibration transmitted from the tool handle to the operator’s wrist, positioned upright, with the elbow bent at 90° angle, was measured. The fixture used to attach the handles to the vibration exciter was designed to eliminate any interruption (disturbance from the base of the shaker). The exciter was set to the frequency range of 0–1000 Hz. Subjects were instructed to grip the handle with constant force. The experiment was initiated once the subject attained the correct posture. The accelerometer was calibrated according to the ISO 16063-21, 2003 and ISO 5347-14, 1993.

2.8 Data analysis

Results were uploaded to a spreadsheet and processed using the IBM SPSS Statistics 20 software^® package. The data was analyzed for vibration acceleration in RMS at 1/3 octave band frequency in the range of 4–1000 Hz for each trial, in accordance with the ISO 5349-2 (2001), and Frequency-weighted RMS acceleration (a_hwx, a_hwy and a_hwz) was calculated for each axis. For each subject, the average of two trials was calculated. The vibration total value (a_hv) was evaluated for each subject using the frequency-weighted RMS vibration acceleration of the axes. The average vibration acceleration across all subjects was calculated. The average vibration total value (a_hv) of each individual prototype handle was subtracted from the a_hv of the reference handle to determine the reduction in vibration achieved.

Subjects rested their arms for a period of time (15 minutes) between the trails. During the rest period, the subjects were asked to rate the handle based on their perception of comfort, specifically, ease of holding the tool, and vibration. Subjective scores were computed using the Borg Scale of Perceived Exertion (CR-10) [41]. The CR-10 scale assessed the perception of intensity as a 10-point linear-scale from 0 (very comfortable to hold/no vibration) to 10 (very uncomfortable to hold/maximum vibration). The difference in frequency-weighted RMS acceleration and vibration of each prototype handle compared to handle A, was calculated using a one-way analysis of variance (ANOVA) and t-test.

3 Results and discussion

The vibration transmitted to the subjects’ wrists was recorded in the X_h, Y_h and Z_h directions at a frequency 0–1000 Hz and a sample rate of 2048 per second (Figs. 7-8). Figure 7 shows the relationship between time and amplitude and Fig. 8 shows the relationship between frequency and acceleration.

Fig.7

Sample graph between amplitude and time.

Fig.8

Sample frequency spectra measured in the X_h, Y_h and Z_h axes at the wrist of the subject.

3.1 Frequency un-weighted analysis

The vibration RMS acceleration without frequency weighting, measured for each handle in the X_h, Y_h, and Z_h-axes, is reported in Fig. 9. Figure 9a–9c shows that all the handles’ vibration responses follow identical patterns. Their resonance frequencies were 10 Hz, 20 Hz and 31.5 Hz. In the X_h-axis (Fig. 9a), the peak accelerations, at a frequency of 10 Hz, for handles A–E respectively were: 26.02 m/s², 13.26 m/s², 16.68 m/s², 23.42 m/s², 30.54 m/s², and 22.94 m/s² for handles F and G. The peak acceleration was at a maximum for handle E and minimum for handle B.

Fig.9

Frequency un-weighted vibration acceleration (RMS) for seven different types of handle design in different axes: (a) X_h-axis, (b) Y_h-axis, (c) Z_h-axis.

In the Y_h-axis the peak vibration acceleration was observed at a frequency of 10 Hz for all the handles, with the exception of handle B, that was31.5 Hz (Fig. 9b). The peak accelerations for handles A-G respectively were: 14.03 m/s², 11.98 m/s², 12.45 m/s², 23.04 m/s², 13.42 m/s², 17.91 m/s² and 17.48 m/s².

Figure 9c shows the peak vibration acceleration for all handles in the Z_h-axis at a frequency of 10 Hz. The peak accelerations for handles A–G respectively were: 34.68 m/s², 29.28 m/s², 30.36 m/s², 27.22 m/s², 26.66 m/s², 29.98 m/s² and 33.18 m/s².

Dewagan KN (2009) studied the relationship between un-weighted vibration acceleration and frequency in the X_h, Y_h and Z_h-axes in different hand-tractor transporting conditions [42]. The resonance frequencies of un-weighted RMS accelerations were found to be 10 Hz, 20 Hz and 31.5 Hz in all the three axes, similar to the findings from the present study. In a study of grass trimmer prototype handles, the frequency of un-weighted RMS peak acceleration was observed at 80 Hz, because the hand grip was not considered [43].

3.2 Frequency-weighted analysis

In order to identify the frequencies associated with injury to the hand-arm system, the frequency weighted RMS acceleration (a_hwx, a_hwy and a_hwz) was calculated for the handles using the filter recommended by the ISO 5349-2 (2001). The frequency weighted RMS acceleration observed in the X_h, Y_h, and Z_h-axes was 10 Hz (Fig. 10).

Fig.10

Frequency weighted vibration acceleration (RMS) for seven different type handle design in different axes: (a) X_h-axis, (b) Y_h-axis, (c) Z_h-axis.

In the X_h-axis the peak accelerations for handles A-G respectively were: 24.70 m/s², 12.62 m/s², 15.94 m/s², 22.32 m/s², 29 m/s², 21.80 m/s² and 21.84 m/s² (Fig. 10a). In the Y_h-axis, the peak accelerations for handles A–G respectively were: 13.37 m/s², 11.43 m/s², 11.88 m/s², 22 m/s², 12.74 m/s², 17.02 m/s² and 16.66 m/s² (Fig. 10b). In the Z_h-axis (Fig. 10c), the peak accelerations for handles A–G respectively were: 33.06 m/s², 27.98 m/s², 28.94 m/s², 25.92 m/s², 25.36 m/s², 28.52 m/s² and 31.6 m/s².

The maximum frequency-weighted vibration acceleration was observed in the Z_h-axis, the dominant direction, followed by the X_h and Y_h-axes. The results from studies on the use of coating over drilling machine handles also found the dominant direction to be the Z_h-axis followed by X_h and Y_h-axes [23]. Figure 10 demonstrates how handles had a higher magnitude of vibration acceleration at lower frequency. A similar response was obtained across tractor handle and grass trimmer handles studies where higher magnitudes of vibration acceleration were observed at lower frequencies and lower magnitudes of vibration at higher frequencies [42, 43].

3.3 Vibration total value (a_hv) analysis

The vibration total value a_hv, being the amalgamation of vibration in all three translational axes, was determined according to ISO 5349-2, 2001, [44, 45]. The mean and standard deviation of frequency-weighted RMS acceleration is presented in Table 3. The average acceleration for handle A in the Z_h-axis was 16.6%; this was 37.4% higher than the X_h and Y_h-axes. Similarly, the average acceleration for handle B in the Z_h-axis was 24%, 28.6% higher than the X_h and Y_h-axes. The average accelerations in the Z_h-axis for handles C-G respectively were: 32.2%, 40% 27.7%, 58.2%, 7.6%, and 3.2%. The vibration acceleration across the X_h, Y_h, Z_h axes was significant at the 1% level for handle A. Of all the prototypes, handle B produced the lowest vibration total value, followed by C, F, D, E and G.

Fig.11

Vibration acceleration reduction for each axis and vibration total value (a_hv) compared with reference handle A.

Table 3

Weighted vibration acceleration (RMS) by axis (a_hwx, a_hwy and a_hwz), vibration total value (a_hv) and ANOVA analysis for handles A–G

Handle	Vibration acceleration (RMS), m/s² (mean standard deviation)			^ahv (mean standard deviation)	ANOVA Values
	X_h-axis	Y_h-axis	Z_h-axis		X_h Vs Y_h	X_h Vs Z_h	Y_h Vs Z_h
A	2.101 (0.550)	1.576 (0.080)	2.519 (0.609)	3.713 (0.824)	0.525^*	–0.418^*	–0.943^*
B	1.604 (0.495)	1.507 (0.188)	2.113 (0.365)	3.171 (0.643)	0.097	–0.509	–0.606
C	1.691 (0.308)	1.017 (0.069)	2.495 (0.286)	3.232 (0.425)	0.674	–0.804	–1.478
D	2.015 (0.345)	1.604 (0.118)	2.115 (0.362)	3.362 (0.513)	0.411	–0.1	–0.511
E	1.893 (0.264)	1.094 (0.288)	2.620 (0.207)	3.443 (0.442)	0.799	–0.727	–1.526
F	2.002 (0.451)	1.426 (0.113)	2.168 (0.479)	3.306 (0.667)	0.576^*	–0.166^*	–0.742
G	2.190 (0.621)	1.396 (0.215)	2.263 (0.598)	3.521 (0.888)	0.794	–0.073	–0.867

^*Significant (p < 0.01).

3.4 Vibration reduction analysis

Reduction in vibration was calculated as the difference between the vibration total value of handle A and the vibration total values of handles B through G. Vibration total value was significantly reduced (p < 0.01) for all 6 prototype handles (Table 4). Table 5 shows the percentage of vibration acceleration reduced by the prototype handles, in the X_h, X_{h_} and Z_h-axes. The reduced vibration total value for handles B through G respectively were: 0.542 m/s² (14.59%), 0.481 m/s² (12.95%), 0.351 m/s² (9.45%), 0.270 m/s² (7.27%), 0.407 m/s² (10.96%) and 0.192 m/s² (5.17%) (Table 5).

Table 4
T-test values associated with the difference in vibration acceleration between handle A and prototype handles B–G

Combined differences between handles t-values

X_h-axis Y_h-axis Z_h-axis ^a hv

A-B 1.325^* 0.478^* 1.676^* 1.300^*

A–C 1.482 3.083 0.130 1.504

A–D 0.563^* –0.223^* 1.563 1.611^*

A–E 2.628 3.279 –1.860 1.972

A–F 1.233^* 0.926 1.944 2.297

A–G –1.037 1.011 2.622 1.538

Combined differences between handles	t-values
A-B	1.325^*	0.478^*	1.676^*	1.300^*
A–C	1.482	3.083	0.130	1.504
A–D	0.563^*	–0.223^*	1.563	1.611^*
A–E	2.628	3.279	–1.860	1.972
A–F	1.233^*	0.926	1.944	2.297
A–G	–1.037	1.011	2.622	1.538

^*Significant (p < 0.01).

Table 5

Percentage of vibration acceleration reduction between handle A and prototype handles B–G

Handle	X_h-axis	Y_h-axis	Z_h-axis	^a hv
B	0.497 (23.7%)	0.069 (4.37%)	0.406 (16.12%)	0.542 (14.59%)
C	0.410 (19.51%)	0.559 (35.46%)	0.024 (0.95%)	0.481 (12.95%)
D	0.086 (4.09%)	–0.028 (–1.77%)	0.044 (16.03%)	0.351 (9.45%)
E	0.208 (9.90%)	0.482 (30.58%)	–0.101 (–4.01%)	0.270 (7.27%)
F	0.099 (4.71%)	0.150 (9.51%)	0.351 (10.96%)	0.407 (10.96%)
G	–0.089 (–4.23%)	0.180 (11.42%)	0.256 (10.16%)	0.192 (5.17%)

3.5 Subjective rating

The subjective rating of comfort and perception of vibration were measured using the Borg Scale of Perceived Exertion (Table 6) [46]. The perception of comfort was highest for handle A followed by handle D, B, C, E, F and G (Table 6). There was no correlation between the comfort ratings and levels of vibration measured (Table 3). Vibration perception was highest (3.4), for the handle perceived as most comfortable, handle A. The subjective comfort rating reflected grip-diameter size.

Table 6
Subjective ratings of comfort perception and vibration perception

Handle Borg’s Scale of Perceived Exertion (Standard Deviation)

Comfort perception Vibration perception

A 5.6 (1.342) 3.4 (0.548)

B 3.8 (0.837) 2.8 (1.304)

C 3.6 (1.342) 3.2 (0.837)

D 4.2 (0.837) 3.0 (0.707)

E 2.8 (0.837) 2.8 (0.837)

F 1.6 (0.548) 2.4 (1.140)

G 1.0 (0.612) 1.5 (1.000)

Handle	Borg’s Scale of Perceived Exertion (Standard Deviation)
A	5.6 (1.342)	3.4 (0.548)
B	3.8 (0.837)	2.8 (1.304)
C	3.6 (1.342)	3.2 (0.837)
D	4.2 (0.837)	3.0 (0.707)
E	2.8 (0.837)	2.8 (0.837)
F	1.6 (0.548)	2.4 (1.140)
G	1.0 (0.612)	1.5 (1.000)

The vibration perception for handle C, D and F respectively, was 3.2, 3.0, and 2.4. While handle G had the highest vibration total value (a_hv), it was perceived to have the lowest vibration. The data elucidates operators’ lack of awareness to the levels of hand-arm vibration being transmitted to their upper-extremity; this is consistent with the literature [43, 47].

3.6 Study limitations

This study did have certain limitations. The prototype handle shapes can be effectively influenced in the bare hand operations. However, the shapes of the handles can’t be influenced in gloved hand operations. The prototype handles were fabricated for 50th percentile people though it is not suitable for 5th percentile and 95th percentile people because of hand size variations. The contribution of finger force were not considered in this study and the future studies should examine the finger forces using the prototype handles developed in this study.

4 Conclusions

Tool handle design influences factors including the shape, size, and perceived comfort by the tool operator, as well as the amount of vibration transmitted to the hand. Improvements in tool comfort can be achieved by considering the anatomy of the hand during handle development. Our prototype Handle B, was found to have transmitted the lowest vibration total value (a_hv) of all the prototype handles. Improved vibration control at the tool level would be useful for the prevention of hand-arm vibration syndrome seeing as tool operators are unable to perceive the relative level of vibration being transmitted to their hands.

Conflict of interest

None to report.

Footnotes

Acknowledgments

The authors wish to extend sincere thanks to all the subjects who have participated in this research. This research work was supported by the grant of Department of Science and Technology (DST, India) Reference No. YSS/2014/000715.

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Handle	Borg’s Scale of Perceived Exertion (Standard Deviation)
	Comfort perception	Vibration perception
A	5.6 (1.342)	3.4 (0.548)
B	3.8 (0.837)	2.8 (1.304)
C	3.6 (1.342)	3.2 (0.837)
D	4.2 (0.837)	3.0 (0.707)
E	2.8 (0.837)	2.8 (0.837)
F	1.6 (0.548)	2.4 (1.140)
G	1.0 (0.612)	1.5 (1.000)