Characterizing the Effects of Explosive Ordnance Disposal Operations on the Human Body While Wearing Heavy Personal Protective Equipment

Abstract

Objective

To provide a comprehensive characterization of explosive ordnance disposal (EOD) personal protective equipment (PPE) by evaluating its effects on the human body, specifically the poses, tasks, and conditions under which EOD operations are performed.

Background

EOD PPE is designed to protect technicians from a blast. The required features of protection make EOD PPE heavy, bulky, poorly ventilated, and difficult to maneuver in. It is not clear how the EOD PPE wearer physiologically adapts to maintain physical and cognitive performance during EOD operations.

Method

Fourteen participants performed EOD operations including mobility and inspection tasks with and without EOD PPE. Physiological measurement and kinematic data recording were used to record human physiological responses and performance.

Results

All physiological measures were significantly higher during the mobility and the inspection tasks when EOD PPE was worn. Participants spent significantly more time to complete the mobility tasks, whereas mixed results were found in the inspection tasks. Higher back muscle activations were seen in participants who performed object manipulation while wearing EOD PPE.

Conclusion

EOD operations while wearing EOD PPE pose significant physical stress on the human body. The wearer’s mobility is impacted by EOD PPE, resulting in decreased speed and higher muscle activations.

Application

The testing and evaluation methodology in this study can be used to benchmark future EOD PPE designs. Identifying hazards posed by EOD PPE lays the groundwork for developing mitigation plans, such as exoskeletons, to reduce physical and cognitive stress caused by EOD PPE on the wearers without compromising their operational performance.

Keywords

physical work testing and evaluation skilled performance bomb suit physiological measurement

Introduction

Explosive ordnance disposal (EOD) technicians have a dangerous job, ranging from dealing with old dynamite, civil war-era cannonballs, and souvenir hand grenades to operating in meth labs and disabling terrorist improvised explosive devices (IEDs). The exponential increased use of IEDs in the past two decades to attack military personnel and civilians (Barker, 2011; Roeder & Schulman, 2010; Wilson, 2007) further signifies an increased role for EOD technicians in both combat and noncombat areas across the globe. To address this growing threat and others alike, there is a continuing need to develop improved personal protective equipment (PPE) for armed forces that is comfortable and less restrictive as the threats of IEDs continue to evolve (Larsen et al., 2011). EOD PPE, often referred to as bomb suits, are designed to protect wearers against blast effects, including blast overpressure, fragmentation, thermal effects, and impacts. To provide the protection needed, significant amounts of ballistic armor and impact absorbing materials are used in EOD PPE that typically cover the entire body, contributing to its weight and bulkiness (Stewart et al., 2011).

Required features of EOD PPE may pose physical stress on the human body during operations. The overall weight, weight distribution (dominant above the shoulders due to the helmet), and high coverage make EOD PPE difficult to maneuver in. As a consequence of its weight and restrictive nature, EOD PPE exacerbates exertion (Stewart et al., 2014) during mission execution, and the technicians must work harder in order to maintain a set work pace and agility (Joseph et al., 2018; Larsen et al., 2011). Similar research on military tactical body armor and firefighter PPE has shown that mobility and movement patterns are altered due to the addition of protective clothing on wearers (Coca et al., 2010; Majumdar et al., 2010; Park et al., 2013). Undesired movement alteration can potentially increase the risks of musculoskeletal injuries, which impacts readiness and performance of the units and may lead to long-term disability of military personnel (Larsen et al., 2011).

Aside from impacts on body and motor functions, physical exertion has been shown to have negative effects on reasoning and decision-making (Weippert et al., 2018), critical capabilities that EOD technicians require in their missions. Heat stress is a more common concern for cognitive functions. For example, heat stress might influence technicians to make decisions more quickly, more frequently, but less accurately (van den Heuvel et al., 2017). Heat stress caused by military and nonmilitary protective clothing has been extensively evaluated as noted by recent reviews (Larsen et al., 2011; McLellan et al., 2013). However, heat stress caused by EOD PPE has not been sufficiently addressed (Stewart et al., 2014). There have been reported occasions where heat stress has caused EOD technicians to become confused or exhibit irrational behavior (Stewart et al., 2011). Previous research may have been completed with a bias, as most research has been completed with a preconceived notion that heat stress does affect cognitive performance (van den Heuvel et al., 2017) and might ignore the effects of physical exertion, which was proven to be a significant factor for a compromised cognitive function (Stewart et al., 2014). Heat stress on cognitive functions is complex and can be task or personnel dependent, making it difficult to distinguish each factor (Hancock & Vasmatzidis, 2003). Nonetheless, more research into how performing physical activities with worn EOD PPE affects cognitive performance should be considered when assessing the human responses during EOD operations.

How an EOD technician responds physiologically to the bulky EOD PPE during EOD operations is relatively less understood when compared with the knowledge of material design of EOD PPE currently available. There is no testing and evaluation protocol available that includes measures of cardio, muscles, and brain simultaneously. The latest bomb suit equipment standard (Public Safety Bomb Suit Standard, NIJ Standard-0117.01, National Institute of Justice, 2016) contains test methods and requirements focusing on the material performance and the ability of the person wearing the suit to complete relevant tasks. A methodology for assessing blast protection in EOD PPE considering injury criteria was also published to better evaluate various suit designs (Bass et al., 2005). While using tests that assess material performance and blast injury mitigation is appropriate to gage effectiveness of EOD PPE, there are no readily available tests for investigating potential health risks of EOD operations, such as load carriage and weight-bearing activities, which may contribute to musculoskeletal injury (Andersen et al., 2016), at this time. It is also important to understand how cardiovascular strain can influence the physiological responses (Costello et al., 2015; Stewart et al., 2014) and what ways that might impact task performance including mobility and cognition (Larsen et al., 2011). Protective clothing weight ranging from 3.51 to 7.00 kg has been found to cause metabolic rate increases of 2.4%–20.9% compared with a control condition (tracksuit bottoms, sweatshirts and trainers, weighing 1.4 kg; Dorman & Havenith, 2009). It is reasonably assumed that EOD PPE, which weighs up to 32 kg, might cause a larger increase in metabolic rate and warrant a detailed investigation. That being said, to assess the all-around impact of EOD PPE, we should consider how the wearer physiologically adapts to maintain physical and cognitive performance, which are equally critical for EOD operations. Therefore, the objective of this study was to provide a comprehensive characterization of EOD PPE by evaluating its effects on the human body during the poses, tasks, and conditions under which EOD operations are performed.

Methodology

Participants

A repeated measures design with one independent variable (two conditions: no EOD versus EOD) was used in this study. Fifteen participants from local bomb squad teams and Army Reserve Officers’ Training Corps (ROTC) university students were included in the study. One participant, who had an incomplete session due to a malfunctioning device, was excluded from all further analysis. Data from fourteen participants (two females and 12 males) are reported here. The inclusion criteria were (1) age between 19 and 60 years; (2) body height between 62 and 74 inches in order to fit in the available EOD PPE (size Medium-Small, size Medium, and size Large); (3) self-report exercise regularly; (4) ability to complete the warm-up activities, including flexing arms and legs, jumping in place, squatting down and up, etc. addressed in Public Safety Bomb Suit NIJ Standard 0117.01 (Public Safety Bomb Suit Standard, NIJ Standard-0117.01, National Institute of Justice (2016)); and (5) ability to carry 31.75 kg of load distributed across the body. The exclusion criteria were (1) any known neuro-musculoskeletal injuries occurring within 1 year prior to recruitment; (2) any cardiovascular disorders such as uncontrolled high blood pressure; (3) self-reported claustrophobia; and (4) any self-disclosed emotional instability, such as mood disorders or depression. The average means and standard deviations, given in parentheses, of age, height, and weight of recruited participants who completed the experiment were 31.62 (10.60) years old, 175.40 (8.88) cm, and 82.04 (14.73) kg, respectively. The time the recruited participants have served as a bomb technician ranged from 0 to 18 years with an averaged 6 years of service. This study complied with the tenets of the Declaration of Helsinki and was approved by the Institutional Review Board of the University of Massachusetts Lowell (#19–023).

Tasks and Experimental Setup

To examine the difference in human performance with and without wearing EOD PPE, two conditions (no EOD versus EOD) were implemented in a single day. The task sequence included in both conditions was identical and performed indoors in an air-conditioned building with the temperature set at 72 °F. Each participant first performed the task sequence without wearing the EOD PPE (no EOD condition) followed by wearing the EOD PPE (EOD condition), with a sufficient break between the two conditions according to the participant’s need. During the EOD condition, participants wore the Med-Eng™ EOD8 suit and EOD9 helmet (Med-Eng, Ottawa, ON, Canada). The suit consisted of a jacket, trousers, a groin protector, and a helmet (the suit weighs about 25.4 kg and the helmet weighs about 5.4 kg). Participants’ base ensemble consisted of a t-shirt, shorts, socks, and underwear. Participants were asked to wear comfortable footwear such as running shoes. (Figure 1A).

Figure 1

Each participant wore a comfortable base ensemble with sensors secured on the body. Selected sensors are shown in the pictures. (A) dashed boxes indicate EMG sensors and dotted boxes indicate inertial measurement unit (IMU) sensors. A portable expired gas analysis device mask was fitted over the participant’s mouth and nose through the cutoff of the helmet visor. (B) The gas chamber was attached to the back of the EOD PPE during the EOD condition. Note. EMG = electromyography; EOD = explosive ordnance disposal; PPE = personal protective equipment.

Each task sequence included two segments: mobility and inspection. Mobility involved picking up a case and walking over various obstacles that might be encountered during EOD operations. Inspection involved kneeling onto the force plates and performing object manipulation and inspection followed by memory tasks while in the kneeling position. In each condition, the task sequence was repeated three times, constituting three trials. A break and water were provided after each trial and as requested by participants.

Mobility tasks took place in our designed test course (Figure 2). The mobility segment started with a participant picking up a 9.75 kg case (weight comparable to the X-ray machine for EOD operations) and walking through a closed door. That participant then continued through a series of obstacles including (1) a tall hurdle (68.58 cm), (2) up and down inclines (15° incline), (3) up and down stairs (5 steps each, 35° slope), and (4) a short hurdle (30.48 cm) in a forward motion. After a set of obstacles, the participant was asked to walk backward on flat ground, and over a tall hurdle and then walk forward again on the flat ground and over a tall hurdle. They finished by walking through an open door to end a single trial of the mobility segment. The selection of 68.58 cm for the tall hurdle and backward motions are based on NIJ standard for a standard guardrail (Public Safety Bomb Suit Standard, NIJ Standard-0117.01, 2016). During a single trial of the mobility segment, participants traversed approximately 100 m.

Figure 2

Mobility test course (~100 m). One trial of the mobility segment: Start → picking up a ~ 9.75 kg case (weight comparable to X-ray machine for EOD operation) → walking through a closed door → walking → tall hurdle → incline and decline → walking and turning → stairs → short hurdle → walking and turning to face the door → walking backward → over the tall hurdle backward → over the tall hurdle forward → walking forward → door → walking → End. Note. EOD = explosive ordnance disposal.

The inspection segment included object manipulation and inspection followed by a computer-based memory task. The participant was instructed to step onto the first force plate, kneel down onto the second force plate using their preferred strategies, and to get ready for the inspection tasks (Figure 3). The first inspection segment (Figure 3B) required a participant to manipulate an object that contains four alphabetically labeled targets inside of tubes with caps. Without moving the base, the participant removed the caps in alphabetical order, inspected the direction of the contained Landolt Cs, gestured the direction of the C using the same hand, and then replaced the cap before inspecting the next target. The second inspection segment, a computer-based memory task, involved performing N-back tests (Herff et al., 2013): 0-back, 1-back, and 2-back were used in the first, second, and third trials, respectively, increasing complexity as the test session progressed. During the N-back test, participants were presented with a sequence of 73 letters and had to indicate when the current letter matches the target letter shown before the sequence (0-back) or the one from N positions earlier in the sequence (1-back and 2-back) by pressing the space bar on the computer (Figure 3C). As N increases, the test gets more difficult and requires increased concentration and memory. In the sequence of 73 letters, each letter appeared for 500 ms with a new letter appearing every 2500 ms.

Figure 3

(A) During the inspection segment, the participant stepped onto the first force plate, then kneeled onto the second force plate. (B) He then carefully manipulated and inspected the objects with four targets in alphabetical order by removing the cap, gesturing the seen direction (large “C”), replaced the cap, and moved onto the next targets. (C) Lastly, he performed the N-back test to conclude one trial.

Physiological measurement and kinematic data recording were used to record human physiological responses and performance during all task sequences. A portable expired gas analysis device (Cosmed K5) was used to measure oxygen consumption (VO₂). The K5 was calibrated before each testing day and after it had been on for 45 min, including a flow meter calibration using a 3 L syringe, a scrubber calibration that zeros the CO2 analyzer, a reference gas calibration using the known reference gas (16% O2, 5% CO2, balance nitrogen) and a delay calibration for the breath-by-breath mode used in this study. A chest harness (Equivital EQ02 LifeMonitor) was used to measure heart rate, respiration rate, and skin temperature. The skin temperature was measured by the infrared thermometer sitting in the side pocket of the harness against the participant’s skin 15–20 cm below the auxiliary region. Surface electromyography (EMG) sampled at 2000 Hz was used to detect muscle activations. The EMG sensors (BioNomadix Wireless EMG system, BIOPAC Systems, Inc) were placed on erector spinae (ES), gluteus medialis, rectus femoris, vastus medialis, biceps femoris long head, tibialis anterior, medial gastrocnemius, and soleus bilaterally according to Surface ElectroMyoGraphy for the Non-Invasive Assessment of Muscles (SENIAM, http://www.seniam.org/). A set of inertial measurement unit (IMU) sensors (Opal, APDM) was used to monitor body movement including trunk, shoulders, elbows, wrists, hips, knees, and ankles at a sampling rate of 128 Hz. Our experimental setup provided a rich set of biometric data for muscle activation and body motion; in this article, we focused on the back muscle activation during inspection tasks. Two force plates (AMTI) were used to measure steadiness of posture when performing inspection tasks. The sampling rate for force data was set at 1000 Hz. In this study, we explored back muscle engagement during inspection tasks using the pair of EMG sensors on the ES. The effects of EOD PPE on muscle activation patterns during the mobility tasks are not in the scope of this report. All the sensors were secured using tape or self-adhesive bandages.

After fitting the sensors and before wearing the EOD PPE or performing the task sequence, participants conducted warm-up activities including flexing arms and legs, jumping in place, and squatting to familiarize themselves with the task sequences to perform and to ensure the sensors would not impede body movement. Participants were also provided the opportunity to familiarize themselves with the EOD PPE despite their experience with EOD operations. This involved the participant donning the EOD PPE, walking the test course, squatting, and stretching arms and legs.

Data Processing and Statistical Analysis

Task performance, task completion time, and N-back test accuracy in percentage (Acc.), were measured. Mobility task completion time (T_mobility) is the duration from when the participants picked up the case to when they dropped the case. Inspection task completion times were measured in two ways: time to complete object manipulation (T_manipulation), and time to finish N-back test (T_Nback). Physiological responses, including oxygen consumption, heart rate (HR), respiration rate (RR), and skin temperature (Temp.), were derived from each task. The total oxygen (cumulated VO₂) used in the mobility and inspection tasks was calculated and presented in milliliters (mL). Oxygen consumption during inspection tasks was captured from the last eight participants, as the first several participants reported perceived exertion during the inspection tasks. Oxygen consumption rate (VO₂), and oxygen consumption rate after EOD weight correction (wt-corrected VO₂) were also calculated to account for body mass, task duration time, and EOD PPE weight. Average normalized HR (by the predicted HR) in percentage, average RR (respirations per min, rpm), and averaged Temp. in Celsius were calculated for each task. We also included maximum values of those aforementioned variables (HR_max, RR_max, Temp._max) derived from the third trial of each task. Center of pressure (COP) displacements, including total displacement in the anterior-posterior (AP) direction and in the mediolateral (ML) direction, were derived using signals from both force plates (Exell et al., 2011) to examine the postural stabilities during object manipulation and inspection.

Back muscle activation was measured by the EMG sensors on the bilateral ES during object manipulation and inspection. The linear envelopes (LE) of both muscles were obtained by full‐wave rectification and low‐pass filtering at 10 Hz after feeding the raw data through a 4th order Butterworth band-pass filter (10–350 Hz). The area under the LE during object manipulation and inspection were calculated for the left and right ES. The summation of area from two muscles was then derived for each condition. To examine the difference in muscle activations in the two conditions, we derived the muscle activation ratio of summed area in the EOD condition to the summed area of the no EOD condition. A ratio value larger than 1 indicates that a participant demonstrated higher muscle activations in the EOD condition compared with the no EOD condition.

The Wilcoxon signed-rank test was used for the comparison of variables mentioned above, also listed in Table 1, between the two conditions (no EOD versus EOD). Statistical analyses were performed in SPSS (Version 26) with the level of significance set at p < .05. Data are presented as median and interquartile range (IQR) unless otherwise specified.

Table 1

Task Performance and Physiological Responses During Mobility and Inspection Tasks in No EOD and EOD Conditions

	Variables	No EODMedian (IQR)	EODMedian (IQR)	p	r
Performance	T_mobility (sec)	179.90 (160.20–187.05)	218.10 (197.23–271.30)	.001	.62
	T_manipulation (sec)	40.50 (37.42–48.67)	40.83 (37.25–49.17)	.802	.04
	T_Nback (sec)	428.91 (408.90–435.30)	422.97 (410.73–478.93)	.096	.31
	Acc. (%)	92.50 (89.75–95.25)	93.00 (85.75–96.75)	.753	.06
Mobility	VO₂ (mL/kg/min)	21.03 (19.24–23.66)	29.32 (25.34–31.39)	.001	.62
	wt-corrected VO₂ (mL/kg/min)	-	22.15 (19.39–23.64)	.73	.07
	cumulated VO₂ (mL)	4881.99 (4610.34–5785.48)	7982.15 (7275.25–9346.95)	.001	.62
	HR (%)	63.79 (56.62–67.52)	75.74 (68.86–84.16)	.001	.62
	RR	24.30 (21.47–25.97)	27.53 (26.93–29.89)	.001	.62
	Temp. (°C)	34.79 (34.22–35.56)	36.27 (35.91–36.42)	.001	.62
	HR_max (%)	64.92 (56.48–70.94)	78.66 (72.21–87.93)	.001	.62
	RR_max	24.40 (21.55–26.5)	28.25 (26.88–31.13)	.002	.60
	Temp._max (°C)	35.15 (34.60–35.83)	37.10 (36.79–37.43)	.001	.62
Inspection	VO₂ (mL/kg/min)	6.97 (6.27–8.26)	9.94 (8.60–11.93)	.012	.63
	wt-corrected VO₂ (mL/kg/min)	-	7.65 (6.42–8.70)	.401	.21
	cumulated VO₂ (mL)	2714.65 (2153.97–2871.41)	3453.73 (3196.40–3658.73)	.012	.63
	HR (%)	48.85 (42.77–56.66)	61.92 (51.12–70.55)	.001	.62
	RR	18.42 (16.46–21.91)	23.78 (20.44–25.65)	.001	.62
	Temp. (°C)	35.02 (34.33–35.63)	36.81 (36.58–36.91)	.001	.62
	HR_max (%)	49.76 (44.68–58.76)	66.36 (54.96–73.80)	.001	.62
	RR_max	20.05 (16.83–22.53)	25.00 (21.18–27)	.001	.62
	Temp. _max (°C)	35.35 (34.73–35.83)	37.60 (37.40–37.80)	.001	.62
	COP	0.090 (0.078–0.097)	0.101 (0.094–0.126)	.001	.62
	AP COP	0.049 (0.045–0.054)	0.064 (0.056–0.072)	.001	.62
	ML COP	0.070 (0.064–0.084)	0.075 (0.069–0.103)	.013	.49

Note. T_mobility = mobility tasks time; T_manipulation = object manipulation time; T_Nback = N-back completion time; Acc. = accuracy of N-back test.

Results

Table 1 shows the summary results of task performance and physiological responses during different tasks in the two conditions including p value and effect size (r).

Task Performance

Figure 4 demonstrates time spent in mobility and inspection tests (N-Back and object manipulation) by each participant. Participants spent significantly more time to complete the mobility tasks while wearing EOD PPE (p = .001). There was no statistically significant difference in N-back execution time and accuracy between the two conditions.

Figure 4

Boxplots of task performance in no EOD and EOD conditions including (A) time spent in mobility tasks, (B) object manipulation time during the inspection segment, (C) N-back test completion time, and (D) N-back test accuracy. The box represents the interquartile range with the median bar within the box. The whiskers extend to the most extreme data points. † indicates statistical significance (p < .05). Note. EOD = explosive ordnance disposal.

Physiological Responses During Mobility

As shown in Figure 5, consistent physiological measures effects were observed in all participants when the tasks were performed with EOD PPE. Compared with the no EOD condition, participants consumed significantly more oxygen overall during mobility tasks when wearing EOD PPE (Figure 5A). The oxygen consumption rate was also significantly higher in the EOD condition. However, after correcting for the EOD PPE weight, we did not observe any significant difference between the two conditions (Figure 5B). Compared with the no EOD condition, the average and maximal HR, RR, and Temp. of all participants during the mobility tasks were higher in the EOD condition (Figure 5C–H).

Figure 5

Physiological measures during mobility tasks: (A) cumulated oxygen consumption, (B) oxygen consumption rate with and without EOD PPE weight corrected, (C) average heart rate, (D) maximal heart rate, (E) average respiratory rate, (F) maximal respiratory rate, (G) average skin temperature, and (H) maximal skin temperature. The box represents the interquartile range with the median bar within the box. The whiskers extend to the most extreme data points. The outliers are indicated by the * symbols. † indicates statistical significance (p < .05). Note. EOD = explosive ordnance disposal; PPE = personal protective equipment.

Physiological Responses During Inspection

During the inspection segment, participants responded similarly as during the mobility tasks (Figure 6). Despite missing data, available oxygen consumption data of eight participants demonstrated a consistent difference between the two conditions. Compared with the no EOD condition, participants consumed significantly more oxygen overall when wearing EOD PPE (Figure 6A). The oxygen consumption rate was also significantly higher in the EOD condition. However, after correcting for the EOD PPE weight, we did not observe any significant difference between two conditions (Figure 6B). Compared with the no EOD condition, the average and maximal HR, RR, and Temp. of all participants during the inspection tasks were higher in the EOD condition (Figure 6C–H).

Figure 6

Physiological measures during inspection tasks: (A) cumulated oxygen consumption, (B) oxygen consumption rate with and without EOD PPE weight corrected, (C) average heart rate, (D) maximal heart rate, (E) average respiratory rate, (F) maximal respiratory rate, (G) average skin temperature, and (H) maximal skin temperature. The box represents the interquartile range with the median bar within the box. The whiskers extend to the most extreme data points. The outliers are indicated by the * symbols. † indicates statistical significance (p < .05). Note. EOD = explosive ordnance disposal; PPE = personal protective equipment.

Postural Stability During Inspection Tasks

The total COP displacement as well as AP and ML displacement in the EOD condition were significantly larger than those in no EOD condition (Table 1 and Figure 7A–C). Figure 7D shows the muscle activation ratios of bilateral ES in the EOD condition versus the no EOD condition. The group data showed that the ES muscle activation in the EOD condition was 1.21 (0.62) times higher as compared with the no EOD condition (p = .026).

Figure 7

(A–C) COP displacement and (D) EMG activation ratio of erector spinae during the object manipulation and inspection. The box represents the interquartile range with the median bar within the box. The whiskers extend to the most extreme data points. The outliers are indicated by the * symbols. † indicates statistical significance (p < .05). Note. COP = center of pressure; EMG = electromyography; EOD = explosive ordnance disposal.

Discussion

To our knowledge, this is the first study providing comprehensive metrics that assess relevant personnel (EOD technicians and ROTC fellows) in a test course that simulates the EOD operations involving both mobility and inspection tasks. In this study, the effects that EOD PPE impose on the human body during operations were explored, along with the implications that physical stress might pose on cognitive performance.

According to the previous literature on the relation between energy expenditure and physical activities with carried loads (Faghy & Brown, 2014; Huang & Kuo, 2014; Lloyd & Cooke, 2000; Quesada et al., 2000), increased energy demand is expected when performing physical activities with the added load of EOD PPE. Similar to that found in the study of Bach et al. (2017), we observed higher energy required in mobility tasks with EOD PPE on. In addition, we found additional energy was required even in less physical activities, such as object manipulation and memory tests. Comparable effects that EOD PPE caused in mobility and inspection tasks were observed (effect size r in Table 1). The inspection tasks used in our study did not allow participants to use biomechanical advantages, such as the passive locking mechanism of knee and hip joints to manage body sway during quiet standing (Federolf et al., 2013; Winter et al., 1998), and therefore required more effort to maintain balance and position. This was exacerbated by the bulky suit and heavy helmet worn by the participants, as EOD PPE adds weight and changes the weight distribution on the human body. This phenomenon was further supported by our findings of higher back muscle activation and larger COP displacement with EOD PPE on. We observed about a 20% increase in ES muscle activation. Furthermore, with EOD PPE on, the AP COP changed more than MP COP implying that muscles contributing to the sagittal plan movement might need to work harder. Future studies should include EMG sensors on the neck and upper back muscles to investigate the potential strain of helmet weight, restricted vision field of the helmet, and restricted mobility of EOD PPE on human body during inspections with EOD PPE on.

Power and agility are important for the tasks that must be completed by EOD technicians, so having a suit that impairs these aspects can be detrimental to their safety (Joseph et al., 2018). The construction of EOD PPE might compromise wearers’ mobility, such as reduced range of motion seen in firefighters wearing firefighting PPE (Coca et al., 2010). Spatiotemporal changes of gait have been found when a load was added (Attwells et al., 2006; Bastien et al., 2005; Donelan et al., 2001; Huang & Kuo, 2014; Majumdar et al., 2010; Park et al., 2013) to minimize energy expenditure. In our study, all participants took a relatively longer time to complete mobility tasks when wearing EOD PPE. Participants spent about 40 s more time to complete a ~ 100-m course. The observed movement speed decrement could be due to the participants’ strategy to minimize energy expenditure (Boffey et al., 2019) caused by the weight and stiff layers of protective materials of the EOD PPE. Despite the participants’ reduced speed in the mobility task when wearing EOD PPE, we still observed higher cumulated oxygen consumption. As reported in the literature, metabolic rate increased with movement speed (Bach et al., 2017). The observed increased oxygen consumption in our study might have been higher if we matched the movement speeds in the two conditions.

The Pandolf load carriage equation, or other prediction models for military load carriage performance used for operational planning, might not be appropriate for EOD operations (Bach et al., 2017). This can be due, in part, to the difference in load distributions. The most common way to carry military loads is via rucksack. Rucksacks and typical military tactical armor systems are secured largely on the torso. This placement keeps the load close to the body’s center of gravity, maintaining gait efficiency (Heglund et al., 1995) and avoiding restriction on mobility. Load distributions of EOD PPE, however, place relatively more weight above the shoulder and extremities overall. Another consideration is the EOD operation often contains a variety of tasks that might be different than typical military operations. Our participants demonstrated much higher oxygen consumption than those reported for even ground walking at a comparable speed (Bach et al., 2017), as we included uneven terrains (stairs, ramps, and hurdles) in contrast to solely level ground as mentioned in previous literature. Therefore, future studies should consider both characteristics of participants and the operational tasks in the prediction model for better estimating energy demand for EOD operations.

In our study, we also observed changes in other physiological measurements such as skin temperature, heart rate, and respiration rate. Although skin temperature increased, we cannot conclude that any performance decrements were a result of thermal stress since we did not directly measure core temperature and the relatively short duration of our tasks made significant core temperature changes unlikely. Furthermore, the feedback from our participants indicated that, subjectively, insignificant thermal stress was experienced. Some literature suggests that fatigue and work tolerance when wearing EOD PPE is based on cardiovascular responses to the physical weight rather than thermal strain (Stewart et al., 2014). This is consistent with our findings: if we corrected for the weight of EOD PPE when calculating the oxygen consumption rate (VO₂ -wt. corrected in Table 1), we no longer observed a significant difference in the two conditions. This also further suggests that the weight of EOD PPE might be a major contributor to the increased energy cost during EOD operations. The observed increased skin temperature could be due to metabolism, insulation and physical load of EOD PPE or some combination thereof (Stewart et al., 2011), which we were unable to differentiate in the current study design. This is outside the scope of our current research.

Much of the existing literature involves studies that focus solely on the biomechanical or physiological effects of EOD PPE in mobility tasks. There is little known about the effects of EOD PPE on the inspection function (manipulating and examining a suspicious object)—particularly after traversing a mobility course that mimics the type of activity that may be experienced during EOD operations. EOD technicians often spend long periods of time in the suit, as the searching period can vary greatly, followed by a shorter period where technicians work in close proximity to the explosive (Costello et al., 2015). Because of the insulation and weight of EOD PPE, heat strain might develop during the EOD operation. One of the common symptoms caused by heat strain that EOD technicians need to be wary of is confusion (Hunt et al., 2016) that impedes their inspection performance, such as reaction time. No confusion was reported by our participants. Although the increased time in the N-back tests (part of the inspection tasks) did not reach statistical significance in the current study, it did amount to about 20 s more in the EOD condition. Increased inspection time might have a significant safety impact in the field. Unlike the consistent findings seen in the mobility task, participants either spent less or more time to complete the inspection tasks when wearing EOD PPE. The mixed results of inspection task completion time might imply that cognitive performance was not only influenced by physical stress or heat strain, but that psychological state (Jensen et al., 2019) might factor in the observation, which will need more research in EOD operations.

Due to the busy work schedule and other commitments of the servicemen/women and technicians we recruited, it was very difficult to have them come to our research center for two separate sessions to accommodate the two conditions. This might be a limitation of our research. However, we presumed that the tasks we implemented can be performed easily without EOD PPE. Therefore, we started with the no EOD condition first. Furthermore, we did not put a limit on the length of the break, allowing the participants to determine the time they needed to recover adequately. The average mean break duration between the two conditions was 54.27 min with the range between 41 and 78.5 min. The break time between trials within the two conditions was comparable, at about 11 min. In other words, a sufficient break was allowed to avoid carryover exhaustion effects.

Conclusion

EOD operations pose several stressors on a human body, such as physical burden, cognitive load, and heat strain. Overall, additional oxygen consumption, higher heart rate, faster breathing rate, and relatively higher skin temperature were observed when participants performed EOD operations while wearing EOD PPE. Task performance was also altered with EOD PPE on. The human-centered test matrices generated in this study can be used for planning mitigation strategies, such as utilizing exoskeletons, devising better suits, and so on, to lower the risk of long-term injuries. Our findings suggest that the development of strategies to reduce physical stress and muscle activations during EOD operations is warranted for injury risk reduction. Recent NATO integration of the exoskeleton in the battlefield project confirms the interest in, and relevance of, future work toward integrating exoskeleton capabilities with EOD PPE.

Key Points

The protective capacities of the EOD PPE, and its concomitant additional weight and obstructing characteristics, compromised the mobility task execution speed.

In addition to reduced performance, higher physiological loads were observed when performing EOD operations.

Increased displacement of COP and ES muscle activation indicates that balance is more challenging with EOD during EOD object manipulation and inspection.

Comprehensive human-centered evaluation of EOD operations is critical to better understand the effects of EOD PPE designs or risk mitigation strategies.

A design, either material or other technology, that reduces physical load on a wearer may increase mobility and inspection performance and reduce stress on the wearer.

Footnotes

Acknowledgments

This project is sponsored by the Department of the Army, U.S. Army Combat Capabilities Development Command Soldier Center (W911QY-18-2-0006). The authors thank all participants who took part in the study.

Author(s) Note

The author(s) of this article are U.S. government employees and created the article within the scope of their employment. As a work of the U.S. federal government, the content of the article is in the public domain.

ORCID iD

Yi-Ning Wu

Author Biographies

Yi-Ning Wu is an associate professor in physical therapy and kinesiology at University of Massachusetts Lowell, USA. She earned a PhD in biomedical engineering from the National Cheng Kung University (Taiwan) in 2007.

Adam Norton is the associate director of the New England Robotics Validation and Experimentation (NERVE) Center, USA. He earned a Bachelor’s in Fine Arts from University of Massachusetts Lowell, in 2010.

Michael R. Zielinski is a systems engineer at the US Army Combat Capabilities Development Command Soldier Center, Natick (MA). He earned a bachelor’s in mechanical engineering from University of Massachusetts Amherst, in 1992.

Pei-Chun Kao is an assistant professor in physical therapy and kinesiology at University of Massachusetts Lowell, USA. She earned a PhD in biomechanics from University of Michigan, Ann Arbor, in 2009.

Andrew Stanwicks is a research assistant at the New England Robotics Validation and Experimentation (NERVE) Center, USA. He earned his bachelor’s in exercise physiology from University of Massachusetts Lowell, in 2020.

Patrick Pang is an undergraduate student in the exercise physiology program at University of Massachusetts Lowell, USA.

Charles H. Cring is a research assistant at the New England Robotics Validation and Experimentation (NERVE) Center, USA. He earned his bachelor’s in exercise physiology from University of Massachusetts Lowell, in 2020.

Brian Flynn is a test engineer at the New England Robotics Validation and Experimentation (NERVE) Center, USA. He earned a bachelor’s in robotics engineering from Worcester Polytechnic Institute, MA, in 2016.

Holly A. Yanco is a professor in computer science and director of the New England Robotics Validation and Experimentation (NERVE) Center, USA. She earned a PhD in computer science from Massachusetts Institute of Technology in 2000.

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