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This paper describes a new type of prosthetic knee joint mechanism that is intended to be cost-effective while providing high-level stance phase function to active individuals with a transfemoral amputation. Initial clinical testing suggests that the new knee joint may have some functional advantages over existing technologies in this category.

We have previously proposed the use of "muscle sounds" or mechanomyography (MMG) as a reliable alternative measure of muscle activity with the main objective of facilitating the use of more comfortable and functional soft silicone sockets with below-elbow externally powered prosthesis. This work describes an integrated strategy where data and sensor fusion algorithms are combined to provide MMG-based detection, estimation and classification of muscle activity. The proposed strategy represents the first ever attempt to generate multiple output signals for practical prosthesis control using a MMG multisensor array embedded distally within a silicon soft socket. This multisensor fusion strategy consists of two stages. The first is the detection stage which determines the presence or absence of muscle contractions in the acquired signals. Upon detection of a contraction, the second stage, that of classification, specifies the nature of the contraction and determines the corresponding control output. Tests with real amputees indicate that with the simple detection and classification algorithms proposed, MMG is indeed comparable to and may exceed EMG functionally.

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This study provides new information about the clinical utilization of instrument-assisted prosthetic alignment techniques for individuals with transtibial amputation.

Silicon soft suction sockets (roll-on sleeves) currently used in passive prostheses for below-elbow amputees could also be used in externally powered prostheses, enhancing their functionality and comfort. However, as it is extremely difficult to hold currently used electromyography (EMG) sensors in place reliably within a silicon socket, an alternative measurement of muscular activity as the control input is necessary. Mechanomyography (MMG) is the epidermal measurement of the low-frequency vibrations produced by a contracting muscle. MMG sensors do not have to be in direct contact with the skin. Moreover, the embedding of sensors in the roll-on sleeve may also solve attachment issues, making sensor placement flexible. Therefore the objective was to determine the feasibility of recording MMG signals using silicon-embedded, micro-machined accelerometers. Fifteen embedded accelerometers were excited with predefined vibration patterns. The signal-to-noise ratio (SNR) and frequency response of each sample were measured and compared with those of non-embedded accelerometers. The SNR of embedded samples (approximately equal to 19 dB) was significantly higher than that of non-embedded samples (approximately equal to 12 dB), owing to the considerable mechanical damping effect of the silicon in the 300-900 Hz bandwidth (p=0.0028). This has implications for the application of silicon-embedded accelerometers for externally powered prosthesis control.

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Additive manufacturing (AM) is on the path to transforming the approach to Prosthetics and Orthotics (P&O) manufacturing. Although digitalization of limbs and other body parts is not new to the field, it has not been widely accepted by the industry for various reasons. However, the reliability and precision that AM can attain, and the availability of various materials is improving rapidly. This professional opinion article discusses the ways that AM has changed P&O services, with a specific focus on prosthetic socket manufacturing. Digitalizing P&O services will eventually change the business model used in clinics, which is further explored here.