Sensory-motor deficits associated with below-knee amputation impair reactions to external perturbations. As such, below-knee prosthesis users rely on proactive control strategies to maintain locomotor stability. However, there are trade-offs (metabolic, comfort, etc.) associated with proactive strategies. We hypothesize that because proactive control strategies are costly, prosthesis users and non-impaired participants will use a priori knowledge (timing, direction) of an impending lateral perturbation to make specific gait adaptations only when the timing of the perturbation is known and the adaptation can be temporally-limited. This hypothesis was partially supported. When the perturbation timing was predictable, only prosthesis users, and only on their impaired side, increased their lateral margin of stability during the steps immediately preceding the perturbation when perturbation direction was either unknown or known to be directed towards their impaired side. This strategy should reduce the likelihood of requiring a corrective step to maintain stability. However, neither group exhibited substantial proactive adaptations compared to baseline walking when perturbation timing was unpredictable, independent of perturbation direction knowledge. The absence of further proactive stabilization behaviors observed in prosthesis users in anticipation of a certain but temporally unpredictable perturbation may be partially responsible for impaired balance control.

Left ventricular assist devices (LVADs) are surgically implanted mechanical pumps that improve survival rates for individuals with advanced heart failure. While life-saving, LVAD therapy is also associated with high morbidity, which can be partially attributed to the difficulties in identifying an LVAD complication before an adverse event occurs. Methods that are currently used to monitor for complications in LVAD-supported individuals require frequent clinical assessments at specialized LVAD centers. Remote analysis of digitally recorded precordial sounds has the potential to provide an inexpensive point-of-care diagnostic tool to assess both device function and the degree of cardiac support in LVAD recipients, facilitating real-time, remote monitoring for early detection of complications. To our knowledge, prior studies of precordial sounds in LVAD-supported individuals have analyzed LVAD noise rather than intrinsic heart sounds, due to a focus on detecting pump complications, and perhaps the obscuring of heart sounds by LVAD noise. In this letter, we describe an adaptive filtering method to remove sounds generated by the LVAD, making it possible to automatically isolate and analyze underlying heart sounds. We present preliminary results describing acoustic signatures of heart sounds extracted from in vivo data obtained from LVAD-supported individuals. These findings are significant as they provide proof-of-concept evidence for further exploration of heart sound analysis in LVADsupported individuals to identify cardiac abnormalities and changes in LVAD support.

Background Although technological advances to pump design have improved survival, left ventricular assist device (LVAD) recipients experience variable improvements in quality of life. Methods for optimizing LVAD support to improve quality of life are needed. We investigated whether acoustic signatures obtained from digital stethoscopes can predict patient‐centered outcomes in LVAD recipients. Methods and Results We followed precordial sounds over 6 months in 24 LVAD recipients (8 HeartWare HVAD™, 16 HeartMate 3 [HM3]). Subjects recorded their precordial sounds with a digital stethoscope and completed a Kansas City Cardiomyopathy Questionnaire weekly. We developed a novel algorithm to filter LVAD sounds from recordings. Unsupervised clustering of LVAD‐mitigated sounds revealed distinct groups of acoustic features. Of 16 HM3 recipients, 6 (38%) had a unique acoustic feature that we have termed the pulse synchronized sound based on its temporal association with the artificial pulse of the HM3. HM3 recipients with the pulse synchronized sound had significantly better Kansas City Cardiomyopathy Questionnaire scores at baseline (median, 89.1 [interquartile range, 86.2–90.4] versus 66.1 [interquartile range, 31.1–73.7]; P =0.03) and over the 6‐month study period (marginal mean, 77.6 [95% CI, 66.3–88.9] versus 59.9 [95% CI, 47.9–70.0]; P <0.001). Mechanistically, the pulse synchronized sound shares acoustic features with patient‐derived intrinsic sounds. Finally, we developed a machine learning algorithm to automatically detect the pulse synchronized sound within precordial sounds (area under the curve, 0.95, leave‐one‐subject‐out cross‐validation). Conclusions We have identified a novel acoustic biomarker associated with better quality of life in HM3 LVAD recipients, which may provide a method for assaying optimized LVAD support.

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The left ventricular assist device (LVAD) has emerged as a bridge or alternative to heart transplant in individuals with advanced heart failure. However, the LVAD recipient population currently faces high rehospitalization rates. Remote analysis of precordial sounds in LVAD recipients may improve aftercare through early detection of complications. Prior work on analyses of precordial sounds in LVAD recipients focused on identifying pump thrombosis. Here, we focus on analyzing intrinsic precordial sounds to provide insight into intrinsic cardiac function. We analyzed a dataset of patient-acquired recordings of precordial sounds in LVAD recipients. We developed a signal processing pipeline to separate LVAD-generated sounds from other precordial sounds, making heart sound analysis in LVAD recipients feasible. Unsupervised clustering of features extracted from LVAD-mitigated sounds revealed subgroups of subjects possessing heart sounds with distinct frequency characteristics. The results provide preliminary evidence for the potential utility of exploring heart sound analysis in LVAD recipients for remote monitoring.