Diabetes-adapted insoles are essential in prevention and rehabilitation of foot ulcers in diabetic foot syndrome. However, their manufacture is labour-intensive and costly. Therefore, the study aims to present an alternative method that allows the individual adjustment of the stiffness of the insoles using the finite element (FE) method and subsequent 3D printing. In the study, 3D gait analysis followed by musculoskeletal modelling was used to determine the boundary conditions of a healthy subject for the FE model. While muscle forces are elaborately implemented in most studies, this FE model presented a more efficient way by using ankle moments and joint reaction forces. The deviation between the simulated plantar peak pressure and the experimentally determined using the Pedar system amounted to 234 kPa in the heel area and 30 kPa in the toe area. The stiffness of the individual insole was adjusted by applying soft insole plugs in areas where high plantar pressures occurred during walking. Three different Young’s moduli were analysed in these areas (0.5 MPa, 1.0 MPa, 1.5 MPa). The computer-based approach to adjust the stiffness of an individual insole revealed a plantar peak pressure reduction by 37% in the heel area and by 119% in the toe area with a Young’s modulus of 0.5 MPa. The presented method could be a valuable tool in the cost-efficient development and engineering of subject-specific 3D-printed insoles for patients with diabetic foot syndrome.

Accurate detection of implant loosening is crucial for early intervention in total hip replacements, but current imaging methods lack sensitivity and specificity. Vibration methods, already successful in dentistry, represent a promising approach. In order to detect loosening of the total hip replacement, excitation and measurement should be performed intracorporeally to minimize the influence of soft tissue on damping of the signals. However, only implants with a single sensor intracorporeally integrated into the implant for detecting vibrations have been presented in the literature. Considering different mode shapes, the sensor’s position on the implant is assumed to influence the signals. In the work at hand, the influence of the position of the sensor on the recording of the vibrations on the implant was investigated. For this purpose, a simplified test setup was created with a titanium rod implanted in a cylinder of artificial cancellous bone. Mechanical stimulation via an exciter attached to the rod was recorded by three accelerometers at varying positions along the titanium rod. Three states of peri-implant loosening within the bone stock were simulated by extracting the bone material around the titanium rod, and different markers were analyzed to distinguish between these states of loosening. In addition, a modal analysis was performed using the finite element method to analyze the mode shapes. Distinct differences in the signals recorded by the acceleration sensors within defects highlight the influence of sensor position on mode detection and natural frequencies. Thus, using multiple sensors could be advantageous in accurately detecting all modes and determining the implant loosening state more precisely.

Resultant hip joint forces can currently only be recorded in situ in a laboratory setting using instrumented total hip replacements (THRs) equipped with strain gauges. However, permanent recording is important for monitoring the structural condition of the implant, for therapeutic purposes, for self-reflection, and for research into managing the predicted increasing number of THRs worldwide. Therefore, this study aims to investigate whether a recently proposed THR with an integrated piezoelectric element represents a new possibility for the permanent recording of hip joint forces and the physical activities of the patient. Hip joint forces from nine different daily activities were obtained from the OrthoLoad database and applied to a total hip stem equipped with a piezoelectric element using a uniaxial testing machine. The forces acting on the piezoelectric element were calculated from the generated voltages. The correlation between the calculated forces on the piezoelectric element and the applied forces was investigated, and the regression equations were determined. In addition, the voltage outputs were used to predict the activity with a random forest classifier. The coefficient of determination between the applied maximum forces on the implant and the calculated maximum forces on the piezoelectric element was R² = 0.97 (p < 0.01). The maximum forces on the THR could be determined via activity-independent determinations with a deviation of 0.87 ± 7.29% and activity-dependent calculation with 0.18 ± 3.96% deviation. The activities could be correctly predicted using the classification model with 95% accuracy. Hence, piezoelectric elements integrated into a total hip stem represent a promising sensor option for the energy-autonomous detection of joint forces and physical activities.

Smart implants are intended to achieve a longer lifespan in the future through integrated sensory and therapeutic functions. In this way, insufficient osseointegration and loosening of uncemented total hip replacements should be prevented by electrodes attached to the femoral stem, specifically stimulating bone growth to improve fixation and thus avoiding revision. For this function, an energy source is necessary, whereby an internal, autonomous one is desirable. Accordingly, in a previous study, a piezoelectric element was integrated into an uncemented hip stem to convert mechanical energy into electrical energy. However, the electrical output has only been calculated computationally, while in practical applications, energy losses occur during energy storage. Moreover, there is a lack of research on total hip and knee replacements with integrated piezoelectric elements that evaluate electrical power generation during everyday activities other than gait. Therefore, the present study aimed to experimentally determine the generated average electrical power of an uncemented revision hip stem with equipped piezoelectric element during different everyday activities. Furthermore, the storable energy during the most promising activities was evaluated with a standard energy harvesting (SEH) circuit. A simplified test rig was set up for these measurements. The results indicate that jogging and walking, with an average electrical power of 204 µW and 75 µW, respectively, convert the most energy, followed by stairs up and stairs down. After 20 min of jogging, 20.7 mJ were stored in a 330 µF capacitor, while one hour of walking yielded 12.9 mJ in a 470 µF capacitor. The energy required for two 1 cm long stimulation electrodes is estimated to range from 0.1 mJ (10 µA, 1000 Hz) to 254 mJ (100 µA, 20 Hz) for the recommended daily protocol of three 45 min sessions. Accordingly, the harvested energy of 12.9 mJ may be sufficient to support electrical bone stimulation at up to 20 µA over 20−1000 Hz. To increase the stored energy, significant energy losses in the SEH circuit due to impedance mismatch must be minimized by improving the energy harvesting circuitry.

The authors wish to make the following corrections to their paper