Autor(es): Morales, Isabel ; Martins, Pedro ; Silva, Carolina ; Marques, Arcelina ; Mendes, Joaquim ; Simini, Franco
Data: 2023
Identificador Persistente: http://hdl.handle.net/10400.22/25314
Origem: Repositório Científico do Instituto Politécnico do Porto
Assunto(s): Plantar pressure; Peak plantar pressure; Pressure time integral; DIAPODAL; MyCareShoe; WalkinSense
We compare plantar pressure data obtained by MyCareShoe® (nine sensors), which uses a proprietary variable resistance conductive ink with DIAPODAL (eight sensors), which utilizes standard force sensing resistors. Both sys tems are then compared to WalkinSense®, a well established pressure system that uses eight force sensing piezoresistors. Our objective is to validate the pressure measurements of DIAPODAL. The assessment protocol consisted of different combinations of the three sensing systems (Test 1 to Test 5). We repeated six times of eight steps each, taken by a healthy volunteer. We analized the signals of the eight common loca tions of the three systems. We detected plantar pressure peaks and calculated the pressure time integral. The pressure for DIAPODAL ranged from 43 to 477 kPa, and the pressure time integral from 75 to 375 kPas over the tests. The equivalence of MyCareShoe® and DIAPODAL with WalkinSense®, taken as the standard for peak plantar pressure measurements was found to be 34% for MyCareShoe® and 69% for DIAPODAL. Considering pressure time integral, the equivalence was 92% to DIAPODAL and 68% to MyCareShoe® which confirm consistency. Record ing of simultaneous plantar soles WalkinSense®/ MyCareShoe® and WalkinSense®/DIAPODAL was consistent for repeatability and linearity (Pearson correlation coefficient, > 0.85 in 80% of the eight-stride series). These findings confirm equivalence between force sensing resistors and conductive ink for pressure measurements. A reliable pressure distribution pattern at 100 Hz can therefore be used as basic information to design a multi variable approach to detect foot conditions by means of real time step detection.
