New Internet of Medical Things for Home-Based Treatment of Anorectal Disorders

Randomized controlled trial of an Internet-of-Medical-Things device for patient-guided anorectal biofeedback therapy

Biofeedback therapy is useful for treatment of functional defecation disorders but is not widely available and is labor intensive. We developed an Internet-of-Medical-Things (IoMT) device, enabling self-guided biofeedback therapy. This study assesses the safety and efficacy of self-guided biofeedback therapy using the IoMT device in comparison to standard operator-led therapy. Patients experiencing urge or seepage fecal incontinence (≥1 episode/week) were randomly assigned to either our IoMT system or to the conventional anorectal manometry-based therapy. Both interventions comprised six weekly sessions, focusing on enhancing anal strength, endurance, and coordination. The novel device facilitated self-guided therapy via visual instructions on a companion app. Primary outcomes included safety/tolerability, changes in Vaizey severity scores, and alterations in anorectal pressure profiles. Twenty-five patients (22 females, 3 males) participated, with 13 in the novel device group and 12 in the standard therapy group. Both groups showed significant reductions in symptom severity scores: IoMT device group -4.2 (95% CI: -4.06, -4.34, p = 0.018), and the standard therapy group -4.8 (95% CI: -4.31, -5.29, p = 0.028). Anal sphincter resting pressure and sustained squeeze time improved significantly in both groups, and the novel device group demonstrated an increase in maximum sphincter squeeze pressure. There were no significant differences between the therapy groups. Importantly, the experimental device was well-tolerated compared with standard therapy, with no serious adverse events observed. This study demonstrates the comparable efficacy of self-administered biofeedback using the IoMT device with traditional biofeedback therapy. The results demonstrates the potential of the IoMT device as a safe, self-guided method for FI therapy, offering convenience and effectiveness in fecal incontinence management.

Application of remote fetal heart rate monitoring via internet in late pregnancy during the COVID-19 pandemic

BACKGROUND

Internet-related technologies have rapidly developed and started to impact the traditional medical practices, which combined wireless communication technology as well as "cloud service" technology with electronic fetal heart monitoring have become a mainstream tendency.

OBJECTIVE

To investigate the clinical application value of remote fetal heart rate monitoring mode (RFHRM) on late pregnancy during the coronavirus disease (COVID-19) pandemic.

METHODS

From March 2021 to February 2022, we recruited 800 cases of pregnant women received prenatal examination at the Anhui Province Maternity and Child Healthcare Hospital. These pregnant women were randomly divided into two groups: the control group (n= 400), which was given traditional management, and the observation group (n= 400), which received remote monitoring technology on this basis. The two groups were compared with neonatal asphyxia, pregnancy outcomes, Edinburgh postnatal depression scale (EPDS), prenatal examination expenses and total time consumption.

RESULTS

There were no statistically significant differences between the groups in pregnancy outcome and neonatal outcome (P> 0.05). However, total EPDS score of 12.5% pregnant women in TPE group were higher than 12. The TPE group had significantly higher mean EPDS scores compared with the RFHRM group (7.79 ± 3.58 vs 5.10 ± 3.07; P< 0.05). The results showed a significant difference in maternity expenses (2949.83 ± 456.07 vs 2455.37 ± 506.67; P< 0.05) and total time consumption (42.81 ± 7.60 vs 20.43 ± 4.16; P< 0.05) between the groups.

CONCLUSION

Remote fetal heart rate monitoring via Internet served as an innovative, acceptable, safe and effective reduced-frequency prenatal examination model without affecting the outcome of perinatology of pregnant women with different risk factors.

Heart Rate Variability Control Using a Biofeedback and Wearable System

Heart rate variability is an important physiological parameter in medicine. This parameter is used as an indicator of physiological and psychological well-being and even of certain pathologies. Research on biofeedback integrates the fields of biological application (physiological behavior), system modeling, and automated control. This study proposes a new method for modeling and controlling heart rate variability as heart rate acceleration, a model expressed in the frequency domain. The model is obtained from excitation and response signals from heart rate variability, which through the instrumental variables method and the minimization of a cost function delivers a transfer function that represents the physiological phenomenon. This study also proposes the design of an adaptive controller using the reference model. The controller controls heart rate variability based on the light actuators designed here, generating a conditioned reflex that allows individuals to self-regulate their state through biofeedback, synchronizing this action to homeostasis. Modeling is conducted in a target population of middle-aged men who work as firefighters and forest firefighters. This study validates the proposed model, as well as the design of the controllers and actuators, through a simple experiment based on indoor cycling. This experiment has different segments, namely leaving inertia, non-controlled segment, and actively controlled segment.