Figure: General components of the system. (a) Insole film sensor, (b) EVA lining, (c) prototype in use, (d) 8-wire Ethernet RJ-45 to FPC adapter, (e) electric diagram. Source: Authors.
In a new study from Brazil, researchers developed an Internet-of-Things (IoT)-based gait analysis system employing insole pressure sensors to assess gait kinetics. The system integrates piezoresistive sensors within a left foot insole, with data acquisition managed using an ESP32 board that communicates via Wi-Fi through an MQTT IoT framework (MQTT is messaging protocol for machine-to-machine communication) (see Figure). In this initial protocol study, they conducted a comparative analysis using the Zeno Walkway Gait Mat system (Protokinetics, Havertown, PA), supported by ProtoKinetics Software (PKMAS), to explore the correlation and agreement of data obtained from the insole system. Four volunteers (2 males and 2 females, aged 24–28, without gait disorders) walked along a 10-m Zeno system path equipped with pressure sensors while wearing the insole system. Vertical ground reaction force (vGRF) data were collected over 4 gait cycles. The preliminary results indicated a strong positive correlation (r = 0.87) between the insole and the reference system measurements. A Bland-Altman analysis further demonstrated a mean difference of approximately (0.011) between the 2 systems, suggesting a minimal yet significant bias. These findings suggest that piezoresistive sensors may offer a promising and cost-effective solution for gait disorder assessment and monitoring. However, operational factors such as high temperatures and sensor placement within the footwear can introduce noise or unwanted signal activation. The communication framework proved functional and reliable during this protocol, with plans for future expansion to multi-device applications. Additional validation studies with larger sample sizes are required to confirm the system’s reliability and robustness for clinical and research applications.
Source: Rathke CL, Pimentel VCdA, Alsina PJ, do Espírito Santo CC, Dantas AFOdA. IoT-based wireless system for gait kinetics monitoring in multi-device therapeutic interventions. Sensors. 2024; 24(17):5799. https://doi.org/10.3390/s24175799. Use is CC BY 4.0.
