Technical Intervention for Assessment of Physiological Characteristics as Function of Operating Force in Traditional Agricultural Operations

Hota, Smrutilipi; Tewari, V.K.; Singh, Gajendra; Kumari, Sweeti

doi:10.1007/978-981-15-9054-2_44

Cited by 3 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…HR of the subjects was recorded using an HR monitor (Polar, Finland), and OCR was recorded using K4b2 portable metabolic analyzer (COSMED, Rome, Italy). Actuation forces of the brake and clutch were recorded using a custom-built instrumented foot transducer (IFT) [ 28 , 34 ]. The overall discomfort rating (ODR) of the subjects was recorded on a 10-point psychophysical rating scale (0: no discomfort [ND]; 3: light discomfort [LD]; 4: more than light discomfort [MLD]; 5: moderate discomfort [MD]; 6: more than moderate discomfort [MMD]; 7: uncomfortable [UC]; 10: extreme discomfort [ED]) which is an adoption of Corlett and Bishop technique [ 35 ].…”

Section: Methodsmentioning

confidence: 99%

Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques

Hota

Tewari

Chandel

2023

Sensors

Self Cite

View full text Add to dashboard Cite

Dynamic muscular workload assessments of tractor operators are rarely studied or documented, which is critical to improving their performance efficiency and safety. A study was conducted to assess and model dynamic load on muscles, physiological variations, and discomfort of the tractor operators arriving from the repeated clutch and brake operations using wearable non-invasive ergonomic transducers and data-run techniques. Nineteen licensed tractor operators operated three different tractor types of varying power ranges at three operating speeds (4–5 km/h), and on two common operating surfaces (tarmacadam and farm roads). During these operations, ergonomic transducers were utilized to capture the load on foot muscles (gastrocnemius right [GR] and soleus right [SR] for brake operation and gastrocnemius left [GL], and soleus left [SL] for clutch operation) using electromyography (EMG). Forces exerted by the feet during brake and clutch operations were measured using a custom-developed foot transducer. During the process, heart rate (HR) and oxygen consumption rates (OCR) were also measured using HR monitor and K4b2 systems, and energy expenditure rate (EER) was determined using empirical equation. Post-tractor operation cycle, an overall discomfort rating (ODR) for that operation was manually recorded on a 10-point psychophysical scale. EMG-based maximum volumetric contraction (%MVC) measurements revealed higher strain on GR (%MVC = 43%), GL (%MVC = 38%), and SR (%MVC = 41%) muscles which in normal conditions should be below 30%. The clutch and brake actuation forces were recorded in the ranges of 90–312 N and 105–332 N, respectively and were significantly affected by the operating speed, tractor type, and operating surface (p < 0.05). EERs of the operators were measured in the moderate-heavy to heavy ranges (9–24 kJ/min) during the course of trials, suggesting the need to refine existing clutch and brake system designs. Average operator ODR responses indicated 7.8% operations in light, 48.5% in light-moderate, 25.2% in moderate, 10.7% in moderate-high, and 4.9% operations in high discomfort categories. When evaluated for the possibility of minimizing the number of transducers for physical workload assessment, EER showed moderate-high correlations with the EMG signals (rGR = 0.78, rGL = 0.75, rSR = 0.68, rSL = 0.66). Similarly, actuation forces had higher correlations with EMG signals for all the selected muscles (r = 0.70–0.87), suggesting the use of simpler transducers for effective operator workload assessment. As a means to minimize subjectivity in ODR responses, machine learning algorithms, including K-nearest neighbor (KNN), random forest classifier (RFC), and support vector machine (SVM), predicted the ODR using body mass index (BMI), HR, EER, and EMG at high accuracies of 87–97%, with RFC being the most accurate. Such high-throughput and data-run ergonomic evaluations can be instrumental in reconsidering workplace designs and better fits for end-users in terms of agricultural tractors and machinery systems.

show abstract

Section: Methodsmentioning

confidence: 99%

Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques

Hota

Tewari

Chandel

2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…The body's circulatory stress was assessed using cardiac cost of work (CCW) and cardiac cost of recovery (CCR). Total cardiac cost of work (TCCW) and physiological cost of work (PCW) were computed using the HR value as defined by Hota et al (2021).…”

Section: Methodsmentioning

confidence: 99%

Development of an automated mobile robotic sprayer to prevent workers' exposure of agro‐chemicals inside polyhouse

Jat

Dubey

Potdar

et al. 2023

Journal of Field Robotics

View full text Add to dashboard Cite

Automated spraying practices are inevitable for modern polyhouse management to attain a broader objective of minimizing human exposure to agrochemicals. In the present study, an automated mobile robotic sprayer (AMRS) was developed to combat the increased human intervention and safeguard agricultural workers from potential health hazards. The system mainly comprises embedded sensors (ultrasonic, proximity, XBee) and controllers (Arduino, PLC). The controller drives the system on a piping track between the rows as well as on the head space achieving end-to-end automation for spraying operations. The system performance was evaluated on the tomato crop with respect to the physiological traits, yield and economics. Additionally, the study leveraged response surface methodology to optimize forward speed, spray distance, and working pressure of AMRS on the responses, droplet density, coverage, volume mean diameter (VMD) and application rate. Optimization of forward speed (0.79 km/h), spray distance (250 mm) and working pressure (0.40 MPa) resulted in 90.7 droplets/cm 2 droplet density, 47.1% coverage, 170.2 μm VMD and 86.0 mL/m 2 of application rate. Ergonomic aspects of AMRS were assessed by the parameters, human exposure, discomfort and postural assessment with respect to knapsack sprayer. The working heart rate of 103 beats/ min, work pulse of 12 beats/min, oxygen consumption rate of 916 mL/min and energy expenditure rate of 18.7 kJ/min recorded during the ergonomic evaluation of the AMRS were 25%, 75%, 42%, and 41% lower compared to manual spraying, respectively. Moreover, three-six times higher work pulse, cardiac cost, body part discomfort score and overall discomfort rating were observed which indicated more drudgery involved in manual spraying. State-of-the-art system developed for polyhouses would minimize the drudgery and health hazards, significantly. The system's resilience and effectiveness pave the way for its wider deployment where the use of agrochemicals are prevalent, particularly in small-size polyhouses.

show abstract

A sensor‐based assistive technology for lower‐limb‐disabled agricultural workers and abled female workers for tractor clutch and brake operation

Hota

Tewari

Dhruw

et al. 2023

Journal of Field Robotics

View full text Add to dashboard Cite

Agricultural mechanization although reduces the food demand and supply gap through improved and smart technologies, it also risks the lower‐limb disability of workers due to accidents that restrict them to participate in agricultural operations due to the unavailability of appropriate assistive technologies. The lack of use of ergonomics further minimizes the inclusion of female workers in farming operations. Therefore, this study is focused on the development of a sensor‐based wireless hand control system for tractor clutch and brake operation to assist lower‐limb‐disabled agricultural workers and abled females in tractor operation. Actuation force and speed of conventional clutch and brake pedals were evaluated using an integrated foot transducer and used as a reference for the design of the system (clutch: 92–310 N, 36–43 mm/s; brake: 106–329 N, 57–63 mm/s). The hand control system consists of a transmitter and a receiver node incorporating a single‐board computer, matrix keypad, voltage regulators, relay switches, wireless communication through radio frequency modules, and electric linear actuators connected with the pedals through L‐shaped clips, nuts, bolts, and chains. The response time of the developed system was determined as 100 ms and the stopping distance of the tractor using the hand control system ranged from 44.0 to 190.7 cm at a forward speed of 2.1–7.9 km/h. The ergonomic evaluation measured using the K4b2 oxygen analyzer identified the foot control usage in tractors as high energy consuming (9.7–15.1 kJ/min) compared with the hand control usage (7.3–14.1 kJ/min). Electromyography‐root mean square (EMG‐RMS) of upper limb muscle, extension digitorum was found to be highest (14.76–45.29 µV) and was significantly affected by forward speed, gender, subjects, and type of control (p < 0.01) whereas, EMG‐RMS of other selected upper limb muscles, middle deltoid, flexor carpi radialis, and brachioradialis was not significantly affected by the type of control (foot or hand). Muscle workload of all the muscles was observed within the recommended limit (<30%) during the tractor operation with the developed hand control system. The developed hand control system provides options to bypass foot‐based actuation requirement for lower limb disabled as well as female workers. The novel design requires minimal workplace and operating forces and is inclusive of operator ergonomics.

show abstract

Technical Intervention for Assessment of Physiological Characteristics as Function of Operating Force in Traditional Agricultural Operations

Cited by 3 publications

References 11 publications

Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques

Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques

Development of an automated mobile robotic sprayer to prevent workers' exposure of agro‐chemicals inside polyhouse

A sensor‐based assistive technology for lower‐limb‐disabled agricultural workers and abled female workers for tractor clutch and brake operation

Contact Info

Product

Resources

About