A smart pressure-sensitive insole that reminds you to walk correctly: an orthotic-less treatment for over pronation

Interpretable evaluation for the Brunnstrom recovery stage of the lower limb based on wearable sensors

With the increasing number of stroke patients, there is an urgent need for an accessible, scientific, and reliable evaluation method for stroke rehabilitation. Although many rehabilitation stage evaluation methods based on the wearable sensors and machine learning algorithm have been developed, the interpretable evaluation of the Brunnstrom recovery stage of the lower limb (BRS-L) is still lacking. The paper propose an interpretable BRS-L evaluation method based on wearable sensors. We collected lower limb motion data and plantar pressure data of 20 hemiplegic patients and 10 healthy individuals using seven Inertial Measurement Units (IMUs) and two plantar pressure insoles. Then we extracted gait features from the motion data and pressure data. By using feature selection based on feature importance, we improved the interpretability of the machine learning-based evaluation method. Several machine learning models are evaluated on the dataset, the results show that k-Nearest Neighbor has the best prediction performance and achieves 94.2% accuracy with an input of 18 features. Our method provides a feasible solution for precise rehabilitation and home-based rehabilitation of hemiplegic patients.

The role of foot pressure measurement in the prediction and prevention of diabetic foot ulceration-A comprehensive review

The predominant risk factor of diabetic foot ulcers (DFU), peripheral neuropathy, results in loss of protective sensation and is associated with abnormally high plantar pressures. DFU prevention strategies strive to reduce these high plantar pressures. Nevertheless, several constraints should be acknowledged regarding the research supporting the link between plantar pressure and DFUs, which may explain the low prediction ability reported in prospective studies. The majority of studies assess vertical, rather than shear, barefoot plantar pressure in laboratory-based environments, rather than during daily activity. Few studies investigated previous DFU location-specific pressure. Previous studies focus predominantly on walking, although studies monitoring activity suggest that more time is spent on other weight-bearing activities, where a lower "peak" plantar pressure might be applied over a longer duration. Although further research is needed, this may indicate that an expression of cumulative pressure applied over time could be a more relevant parameter than peak pressure. Studies indicated that providing pressure feedback might reduce plantar pressures, with an emerging potential use of smart technology, however, further research is required. Further pressure analyses, across all weight-bearing activities, referring to location-specific pressures are required to improve our understanding of pressures resulting in DFUs and improve effectiveness of interventions.

Smarter Sole Survival: Will Neuropathic Patients at High Risk for Ulceration Use a Smart Insole-Based Foot Protection System?

OBJECTIVE

This study examined adherence to alert-based cues for plantar pressure offloading in patients with diabetic foot disease.

METHOD AND DESIGN

Participants (n = 17) with in diabetic foot remission (history of neuropathic ulceration) were instructed to wear a smart insole system (the SurroSense Rx, Orpyx Medical Technologies Inc, Calgary, Canada) over a three-month period. This device is designed to cue offloading to manage unprotected sustained plantar pressures in an effort to prevent foot ulceration. A successful response to an alert was defined as pressure offloading, which occurred within 20 minutes of the alert onset. Patient adherence, defined as daily hours of device wear, was determined using sensor data and patient questionnaires. Changes in these parameters were assessed monthly.

RESULTS

Patients demonstrating increased adherence over the course of the study received more alerts (0.82 ± 0.31 alerts/hour) than patients whose adherence did not improve (0.36 ± 0.46 alerts/hour, P = .156). By the final stages of the study, participants who had received at least one alert every two hours were more adherent with offloading than participants who received fewer alerts (52.5 ± 4.1% vs 24.7 ± 22.4%, P = .043). Furthermore, duration of time from alert generation to successful offloading was significantly greater in the group receiving fewer alerts. This was measured in the third month with an effect size Cohen's d = 1.739, P = .043.

CONCLUSION

The results suggest a minimum number of alerts (one every two hours) is required for patients with diabetic neuropathy to optimally respond to offloading cues from a smart insole system.