Mowing Patterns Comparison: Analyzing the Mowing Behaviors of Elderly Adults on an Inclined Plane via a Motion Capture Device

Wu, Bo; Wu, Yuan; Aoki, Yoko; Nishimura, Shoji

doi:10.1109/access.2020.3040418

Cited by 10 publications

(11 citation statements)

References 11 publications

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“…The results showed that different postures were affected significantly (p < 0.05).The average UW speed was measured at 2.29 ± 0.53 m/s, the average SW travel speed was measured at 2.07 ± 0.62 m/s, and the average KHC travel speed was measured at 0.58 ± 0.20 m/s. The average bipedal walking velocity measured during this study was faster than the velocity of children measured in previous studies [12,21,22]. This study focused on individual behavior rather than group behavior, which would be less likely to collide.…”

Section: Discussion and Limitationmentioning

confidence: 63%

“…Following the same calculation, other joints can be obtained. Excluding the angles for the chest and neck, the data for the other joints were collected in pairs (e.g., right and left ankle) 22.…”

Section: Discussionmentioning

confidence: 99%

“…B. Wu et al (2020) collected information from elderly Japanese lawn mowers mowing on an inclined surface using a highly sophisticated motion capture device to compare the hazards of mowing movements under three different working conditions [22]. In addition, some researchers have used motion capture systems to study the gait of children in normal situations (non-emergency situations) [23][24][25][26][27][28][29].…”

Section: Motion Capture Systemmentioning

confidence: 99%

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An Ergonomic Assessment of Different Postures and Children Risk during Evacuations

Jia

Zhang

Gao

et al. 2021

IJERPH

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Crawling is recommended for avoiding high heat and toxic fumes and for obtaining more breathable air during evacuations. Few studies have evaluated the effects of crawling on physical joints and velocity, especially in children. Based on motion capture technology, this study proposes a novel method of using wearable sensors to collect exposure (e.g., mean duration, frequency) on children’s joints to objectively quantify the impacts of different locomotion methods on physical characteristics. An on-site experiment was conducted in a kindergarten with 28 children (13 boys and 15 girls) of different ages (4–6 years old) who traveled up to 22 m in three different postures: upright walking (UW), stoop walking (SW), and knee and hand crawling (KHC). The results showed that: (1) The level of joint fatigue for KHC was heavier than bipedal walking (p < 0.05), which was evidenced by higher mean duration and frequency. There was no significant difference between UW and SW (p > 0.05). (2) The physical characteristics of the children in the different postures observed in this study were different (p < 0.05). The ankle was more fatigued than other joints during bipedal walking. Unlike infants, the wrists and hips of the children became fatigued while crawling. The key actions flexion/extension are more likely to induce joint fatigue vs. other actions. (3) Crawling velocity was significantly slower than the bipedal velocities, and UW was 10.6% faster than SW (p < 0.05). The bipedal walking velocity started to decrease after the children had travelled up to 13 m, while the KHC velocity started to decrease after traveling up to 11.6 m. (4) In a severe fire, the adoption of SW is suggested, as the evacuees can both evacuate quickly and avoid overworking their joints. (5) There were no significant differences in the age (p > 0.05) and gender (p > 0.05) of the children on the joints in any of the three postures. To conclude, KHC causes more damage to body joints compared to bipedal walking, as evidenced by higher exposure (mean duration, frequency), whereas UW and SW are similar in terms of the level of joint fatigue. The above findings are expected to provide a useful reference for future applications in the children’s risk assessment and in the prevention design of buildings.

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Section: Discussion and Limitationmentioning

confidence: 63%

Section: Discussionmentioning

confidence: 99%

Section: Motion Capture Systemmentioning

confidence: 99%

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An Ergonomic Assessment of Different Postures and Children Risk during Evacuations

Jia

Zhang

Gao

et al. 2021

IJERPH

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“…With the continuous development of sensors and Internet of Things (IoT) technologies, most human activities, including body movements [ 7 ], eye movements [ 8 ], and even activities on the Internet [ 9 ], can be dynamically acquired and analyzed. Among them, motion-capture devices, which can save a series of human movements as analyzable data through sensors, have been widely used in a variety of studies.…”

Section: Introductionmentioning

confidence: 99%

“…According to relevant studies [ 11 ] and related interviews with mowers in our previous works [ 7 , 12 ], personal factors such as age and physique may affect the stability of mowing behaviors, especially for physically demanding tasks like mowing on slopes. To ensure the safety of older workers, it is also necessary to study the effects of personal factors on older workers’ body movements while mowing on slopes.…”

Section: Introductionmentioning

confidence: 99%

Analysis on the Subdivision of Skilled Mowing Movements on Slopes

Nishimura

et al. 2022

Sensors

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Owing to the aging of the rural population in the hilly and mountainous areas of Japan, mowing on narrow ridges and steep slopes is done manually by the elderly—individuals over 65 years of age. Studies have shown that many accidents that occurred during mowing were caused by workers’ unstable posture, especially when mowing on steep surfaces where there is a high risk of falling. It is necessary to analyze the body movements of mowing workers to elucidate the elements related to the risk of falls. Therefore, in this study, based on a high-precision motion-capture device and a series of experiments with elderly, skilled mowing workers, we focused on the movements of mowing. We sought to identify effective and safe mowing patterns and the factors that lead to the risk of falls. In various mowing styles, compared to the stride (S) and downward (D) mowing patterns, the basic (B) and moving (M) patterns were the most efficient; however, the risk of falls was also the highest among these patterns. While mowing, workers need to pay more attention to their arm strength and take appropriate measures to reduce the risk of falls according to their age and physique. The results can be used as data for the development of fall-detection systems and offer useful insights for the training of new mowing workers.

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Development of a method for detecting the planting and ridge areas in paddy fields using AI, GIS, and precise DEM

Hamano

Shiozawa²,

Yamamoto³

et al. 2023

Precision Agric

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In Japan, mowing work on ridges of farms that cultivate rice is difficult for farmers, especially in hilly and mountainous areas. Moreover, geographical information on ridges in paddy fields has not been prepared; such information includes the slope angle, the ridge area, and the ridge rate of the total paddy field area. This issue causes a level of uncertainty in management analysis in terms of labor costs, including mowing costs, particularly when farmers and agricultural corporations are starting or expanding farm businesses. Therefore, this research developed a method for creating planting area and ridge area polygons in paddy fields to measure the actual areas of both sites using slope angle information and calculating the ridge rates in paddy fields. This study adopts artificial intelligence, geographical information system (GIS), and precision digital elevation model techniques as strategy implementation tools with data prepared by an aerial laser survey of Nagano Prefecture. The model generated using the proposed machine learning tool can automatically detect the planting and ridge areas of paddy fields through aerial images of farmland with more than 96% accuracy. Then, polygons can be created for use in GIS. Furthermore, these polygons can be created for most of the understudied paddy fields, approximately 35 000 hectares throughout Nagano Prefecture, in only 2 to 3 weeks. Therefore, based on these techniques, the slope angles of ridges, the ridge areas, and the ridge rates of paddy areas can be measured through polygons.

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Mowing Patterns Comparison: Analyzing the Mowing Behaviors of Elderly Adults on an Inclined Plane via a Motion Capture Device

Cited by 10 publications

References 11 publications

An Ergonomic Assessment of Different Postures and Children Risk during Evacuations

An Ergonomic Assessment of Different Postures and Children Risk during Evacuations

Analysis on the Subdivision of Skilled Mowing Movements on Slopes

Development of a method for detecting the planting and ridge areas in paddy fields using AI, GIS, and precise DEM

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