IoT based monitoring of foot pressure using FSR sensor

Malvade, Payal S.; Joshi, Atul; Madhe, Swati

doi:10.1109/iccsp.2017.8286435

Cited by 47 publications

(24 citation statements)

References 10 publications

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“…This spacer was recommended by the manufacturing company to evenly distribute the pressure applied to the sensor [20]. Preliminary tests and also previous work [23,24] have showed that without the use of a spacer on the effective area, a higher measurement error will be produced compared to when a spacer is used. However, the suitable material and dimensions of the spacer to obtain accurate measurements were not specified.…”

Section: Number Of Sensor and Distributionmentioning

confidence: 99%

In-sole plantar pressure device with optimization measurement techniques

Hussein

Hasan

Soh

et al. 2020

IJEECS

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Doctors and clinicians rely on accurate underfoot pressure data to perform diagnosis of foot diseases. In sole pressure measurement systems are designed to provide such data but its implementation suffers from certain constraints such as the need for a spacer to be placed on the sensor when taking measurements and the need for multiple calibrations due to the fact that the sensor parameters tend to change without it. In this work, we proposed an optimization technique to address these limitations. The results obtained from testing indicate that the proposed device performed measurement of plantar pressure effectively. Also, the calculation of body weight using the proposed optimization technique is improved from 5.07% to 9.06%. For validation, the results are compared with the measurements from a commercial plantar pressure device (EMED system) as benchmark. INTRODUCTIONPlantar pressure measurement systems are often used to obtain useful data regarding the structure of the underfoot base and the distribution of pressure it exerts to the surface plane. These systems allow for the diagnosis and treatement of various problems related to posture and gait but there are inherent limitations within these systems that need to be addressed such as the lack of precision in body weight calculation, self-calibration improvements and suitability of the physical characteristics of the materials used. The work in [1, 2] studies the effects of obesity or increasing body weight and the resulting disparities in the plantar pressure distribution patterns. Another study found that increase in the human body weight was a significant factor that contributed to the plantar pressure distribution pattern [3,4]. This leads to recommendation from researchers that the diagnosis and treatment of foot problems in obese patients should consider the effects of increased body mass on their plantar loading [5,6]. The study in [7,8] then found that the relationship between mean/peak plantar pressure and increasing body mass was dependent on the affected plantar area.These prior works show that current insole systems do not consider pressure range in the measurements of plantar pressure. Thus, there is a need for a method to obtain points that can be used to produce a suitable pressure range in the plantar measurement system, specifically the maximum and minimum pressure values during walking and standing, as related to the body mass. The findings of accurate and reliable underfoot pressure ranges based on incremental body weight is needed as a benchmark or

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Section: Number Of Sensor and Distributionmentioning

confidence: 99%

In-sole plantar pressure device with optimization measurement techniques

Hussein

Hasan

Soh

et al. 2020

IJEECS

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“…Pada penelitian sebelumnya digunakan 5 sensor untuk 5 titik tekanan pada kaki [3]. Namun, pada penelitian ini hanya digunakan satu titik saja, yakni titik nomor 5.…”

Section: B Perancangan Sensor Tekananunclassified

Kontrol Kecepatan Motor Sepeda Listrik Menggunakan Force Sensor dan Elektromiografi (EMG)

Gunawan¹,

Rivai²,

Tasripan³

2019

JTITS

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A343Abstrak-Torque Assisted Bicycle (TAB) merupakan sebuah sepeda dengan penambahan motor listrik sebagai bantuan bagi penggunanya. Sepeda TAB ini dapat mempermudah pengguna dalam berkendara dan ramah lingkungan karena tidak menghasilkan gas emisi. Namun, sepeda TAB masih belum terlalu diminati di Indonesia. Salah satu penyebabnya ialah penggunaan sensor torsi yang mahal. Pada penelitian ini sensor tekanan dan sensor EMG digunakan untuk mengganti sensor tersebut. Sensor EMG yang digunakan memiliki keluaran antara 0 -5V single channel dan sensor tekanan menggunakan Force Sensitive Resistor (FSR) dengan keluaran antara 0 -3.5V. Data dari dua sensor ini digunakan untuk mengenali tingkat aktivitas otot dari pengguna dengan menggunakan metode Artifical Neural Network dan metode pembelajaran backward propagation. Dari hasil penelitian yang telah dilakukan, penempatan elektroda optimal untuk sensor EMG pada Vastus Lateralis dan FSR pada bagian medial dari telapak kaki. Dalam pengujian statis, subyek melakukan gerakan mengayuh selama 10 detik dengan beban berupa tekanan dari rem. Hasil pengujian pada empat subyek menghasilkan tingkat ketelitian deteksi aktivitas kaki sebesar 83,33%. Pada pengujian dinamis di permukaan dengan 4 tingkat kemiringan berbeda, sistem mampu mendeteksi beban dengan tingkat ketelitian 75%.Kata Kunci-EMG, ANN, TAB, Sensor Tekanan, Sepeda Listrik.

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“…In [12], five force sensitive resistor (FSR) sensors were used within an insole to count steps accurately under five walking styles (normal walking, jogging, sprint, star ascent, and stair descent), thus providing emergency detection (e.g., falling) for senior people. In [13], a wireless insole system was developed using the four FSRs to analyze how the patient's pressure distribution is affected by abnormalities, fractures, etc. In [6], an insole optical fiber sensor was presented for continuous and remote gait pressure distribution monitoring and to evaluate the evolution of ulcerations for patients of diabetes.…”

Section: Introductionmentioning

confidence: 99%

“…However, there are still some challenges that need to be addressed. First, the limited number of sensing points places a restriction on gait recovery resolution [6,[12][13]. Second, these IoHT gait analysis systems are based on active sensing techniques [6,[12][13], which suffer from high energy consumption, thus limiting their successful use in IoHT architecture.…”

Section: Introductionmentioning

confidence: 99%

A piezoelectric flexible insole system for gait monitoring for the Internet of Health Things

Chen¹,

Dai²,

Gao³

2020

Preprint

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Gait is closely associated with many chronic diseases. With the development of the Internet of Health Things (IoHT), long-term gait monitoring and corresponding analysis can be performed remotely, reducing a patient’s time and traffic cost, while providing doctors more valuable gait information. The presented work provides a feasible means for real-time, long-term, and accurate gait monitoring in an IoHT scenario. Through the experimental results, the high detection sensitivity of 54 mN and responsivity of 163 mV/N are achieved, thereby satisfying the need for analyzing various diseases. Furthermore, 16 hours continuous working time indicates its successful utilization during long-term gait monitoring.

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IoT based monitoring of foot pressure using FSR sensor

Cited by 47 publications

References 10 publications

In-sole plantar pressure device with optimization measurement techniques

In-sole plantar pressure device with optimization measurement techniques

Kontrol Kecepatan Motor Sepeda Listrik Menggunakan Force Sensor dan Elektromiografi (EMG)

A piezoelectric flexible insole system for gait monitoring for the Internet of Health Things

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