Preventing Back Injury in Caregivers Using Real-Time Posture-Based Feedback

Owlia, Mohammadhasan; Ng, Christine; Ledda, Kevin; Kamachi, Megan; Longfield, Amanda; Dutta, Tilak

doi:10.1007/978-3-319-96083-8_90

Cited by 12 publications

(11 citation statements)

References 12 publications

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“…This reflects on instrument-based methods. For instance, [14] monitored the back with one IMU placed on the chest, [10] placed the sensor on the upper back, and [15] used 2 IMUs at the mid-thoracic level and sacrum.…”

Section: B Sensor Placement 1) Imu Placementmentioning

confidence: 99%

“…Owalia et al also explored the potential of providing postural biofeedback to the user and developed the PostureCoach aiming caregiver's training. The system instrumented two IMUs placed at the midthoracic level and in the sacrum to measure the flexion angle of the lumbar spine and provide an auditory warning when the pre-set thresholds were exceeded [15]. Both studies' results evidenced an improvement in the workers' posture and risk awareness, derived from the implemented feedback strategies.…”

Section: Introductionmentioning

confidence: 99%

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Smart Vest for Real-Time Postural Biofeedback and Ergonomic Risk Assessment

2020

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Work-related musculoskeletal disorders (WRMSDs) are a serious worldwide health concern, that can result in the worker's permanent disability and an economic burden of up to 2% of the Gross Domestic Product (GDP). This paper presents the design and development of an innovative smart garment for real-time ergonomic risk assessment. It aims to empower operators with posture awareness and provide objective data to ergonomists. The system is based on inertial sensors and implements a biofeedback strategy that uses haptic stimulus to warn the user about hazard postures, enabling more ergonomic postures. To allow an easy data analysis, a graphical interface was developed in MATLAB. This framework was validated with 5 subjects, in a simulated scenario with 5 tasks that included a collaborative robot arm. The results showed that providing real-time biofeedback to the subject improves posture awareness, and has a significant impact on reducing the ergonomic risk, with reductions of up to 39.8% of the time spent in hazard postures. The wearable technology and developed methodologies are a promising tool to complement the ergonomist diagnoses of hazard tasks and workspaces and to reduce the risk of musculoskeletal disorders. INDEX TERMS Ergonomic risk assessment, biofeedback, inertial measurement units, wearables design, WRMSDs.

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Section: B Sensor Placement 1) Imu Placementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Smart Vest for Real-Time Postural Biofeedback and Ergonomic Risk Assessment

2020

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“…The aforementioned investigations therefore suggest that trunk angle and foot position monitoring and guidance can contribute to the prevention of LBP during manual handling. Previous studies have developed monitoring systems for trunk angle during manual handling [ 10 , 11 , 12 ]. The PostureCoach can measure and provide feedback on trunk angle during manual handling using wearable inertial sensors [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have developed monitoring systems for trunk angle during manual handling [ 10 , 11 , 12 ]. The PostureCoach can measure and provide feedback on trunk angle during manual handling using wearable inertial sensors [ 10 , 11 ]. Training programs using this system can improve the trunk angle of caregivers during manual care activities [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…Previous wearable systems to prevent LBP could monitor and provide feedback for injury risks such as lumbar loads and trunk angles during manual lifting [ 10 , 11 , 12 ]; moreover, other previous studies have also shown that providing feedback regarding trunk angle and lower limb posture can also help to reduce the risk of LBP [ 13 ]. However, even though feedback about the trunk angle was completed in real time, lower limb posture feedback was performed by a personal trainer giving verbal instructions such as “use legs instead of back”.…”

Section: Introductionmentioning

confidence: 99%

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Foot Position Measurement during Assistive Motion for Sit-to-Stand Using a Single Inertial Sensor and Shoe-Type Force Sensors

Kitagawa

Fernandez

Nagasaki

et al. 2021

IJERPH

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Assistive motion for sit-to-stand causes lower back pain (LBP) among caregivers. Considering previous studies that showed that foot position adjustment could reduce lumbar load during assistive motion for sit-to-stand, quantitative monitoring of and instructions on foot position could contribute toward reducing LBP among caregivers. The present study proposes and evaluates a new method for the quantitative measurement of foot position during assistive motion for sit-to-stand using a few wearable sensors that are not limited to the measurement area. The proposed method measures quantitative foot position (anteroposterior and mediolateral distance between both feet) through a machine learning technique using features obtained from only a single inertial sensor on the trunk and shoe-type force sensors. During the experiment, the accuracy of the proposed method was investigated by comparing the obtained values with those from an optical motion capture system. The results showed that the proposed method produced only minor errors (less than 6.5% of body height) when measuring foot position during assistive motion for sit-to-stand. Furthermore, Bland–Altman plots suggested no fixed errors between the proposed method and the optical motion capture system. These results suggest that the proposed method could be utilized for measuring foot position during assistive motion for sit-to-stand.

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