Classification Method of Assistance Motions for Standing-up with Different Foot Anteroposterior Positions using Wearable Sensors

Kitagawa, Kodai; Uezono, Tsuyoshi; Nagasaki, Takayuki; Nakano, Satoshi; Wada, Chikamune

doi:10.1109/ict-robot.2018.8549912

Cited by 4 publications

(5 citation statements)

References 6 publications

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“…In addition, other previous studies used commands such as "use legs instead of back" to improve patient handling motion [17]. Thus, we have been developing a measurement method for foot position using wearable sensors to determine a suitable foot position [22,23]. Our previous method could measure foot position during patient lifting motion (assistance for sit-to-stand), which is part of patient transfer, using inertial sensors and shoe-type force sensors.…”

Section: Introductionmentioning

confidence: 99%

“…Our previous method could measure foot position during patient lifting motion (assistance for sit-to-stand), which is part of patient transfer, using inertial sensors and shoe-type force sensors. However, this method cannot be applied to patient transfer, including twisting and lowering [22,23]. The posture during twisting and lowering should be measured and monitored because twisting and lowering cause lumbar loads on caregivers [5,24].…”

Section: Introductionmentioning

confidence: 99%

“…The posture during twisting and lowering should be measured and monitored because twisting and lowering cause lumbar loads on caregivers [5,24]. In addition, our previous method required the preparation of additional devices because this method requires shoe-type force sensors, which are not common devices [22,23]. On the other hand, inertial sensors can be used by many caregivers because they are installed on common smartphones.…”

Section: Introductionmentioning

confidence: 99%

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Foot Position Recognition Using a Smartphone Inertial Sensor in Patient Transfer

Kitagawa,

Takashima,

Kurosawa

et al. 2024

BioMed

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Caregivers experience lower back pain due to patient transfer. Foot position is an important and adjustable posture for reducing lumbar loads during patient transfer. Specifically, a suitable foot position provides the use of the lower limbs instead of the lumbar region in patient handling. Thus, we have developed a monitoring and feedback system for foot positioning using wearable sensors to instruct suitable foot positions. However, existing measurement methods require multiple specific wearable sensors. In addition, the existing method has not been evaluated in patient transfer, including twisting and lowering. Thus, the objective of this study was to develop and evaluate a measurement method using only a smartphone-installed inertial sensor for foot position during patient transfer, including twisting and lowering. The smartphone attached to the trunk measures the acceleration, angular velocity, and geomagnetic field. The proposed method recognizes anteroposterior and mediolateral foot positions by machine learning using inertial data. The proposed method was tested using simulated patient transfer motions, including horizontal rotation. The results showed that the proposed method could recognize the two foot positions with more than 90% accuracy. These results indicate that the proposed method can be applied to wearable monitoring and feedback systems to prevent lower back pain caused by patient transfer.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Foot Position Recognition Using a Smartphone Inertial Sensor in Patient Transfer

Kitagawa,

Takashima,

Kurosawa

et al. 2024

BioMed

Self Cite

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show abstract

“…Several factors, such as the foot position and arm movement, are useful to achieve suitable postures to prevent lower back pain during patient handling [11][12][13]. Therefore, a simple and wearable system that monitors the trunk angle, foot position, and arm movement is being develop [14].…”

Section: Introductionmentioning

confidence: 99%

“…Our previous study proposed a postural recognition method during sit-to-stand assistive motions but could not consider other patient-handling aspects and various foot positions and arm movements [14]. Several patient-handling aspects, such as providing postural change to turn a patient on a bed, cause lumber load among caregivers [12,15].…”

Section: Introductionmentioning

confidence: 99%

Posture Recognition Method for Caregivers during Postural Change of a Patient on a Bed using Wearable Sensors

Kitagawa¹,

Matsumoto²,

Iwanaga³

et al. 2020

Adv. sci. technol. eng. syst. j.

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Caregivers experience lower back pain due to their awkward postures while handling patients. Therefore, a monitoring system to supervise caregivers' postures using wearable sensors is being developed. This study proposed a postural recognition method for caregivers during postural change while handling a patient on a bed. The proposed method recognizes foot positions and arm movements by a machine learning algorithm using inertial data on the trunk and foot pressure data obtained from wearable sensors. An experiment was conducted to evaluate whether the proposed method could recognize three foot positions and three arm movements. Participants provided postural change for a simulated patient on a bed (patient: supine to lateral recumbent) under nine conditions, including different combinations of the three foot positions and three arm movements; the experiment was repeated ten times for each condition. Experimental results showed that the proposed method using an artificial neural network with all features obtained from an inertial measurement unit and insole pressure sensors could recognize arm movements and foot positions with an accuracy of approximately 0.75 and 0.97, respectively. These results suggest that the proposed method can be used in a monitoring system tracking a caregiver's posture.

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Machine Learning in Student Health - A Review

Gurusamy

Chakrabarti

Chakkaravarthy

2022

2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)

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Classification Method of Assistance Motions for Standing-up with Different Foot Anteroposterior Positions using Wearable Sensors

Cited by 4 publications

References 6 publications

Foot Position Recognition Using a Smartphone Inertial Sensor in Patient Transfer

Foot Position Recognition Using a Smartphone Inertial Sensor in Patient Transfer

Posture Recognition Method for Caregivers during Postural Change of a Patient on a Bed using Wearable Sensors

Machine Learning in Student Health - A Review

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