An accuracy-configurable adder (ACA) meets various requirements in energy efficiency and accuracy of many applications. However, it suffers from problems such as a large hardware cost for performing configurations. In this article, we propose two energy-efficient transistor-level accuracy-configurable full adders, referred to as a positive ACA (PACA) and a negative ACA (NACA). Each design uses only two transistors as switches driven by an enable signal to configure the accurate and approximate modes. Dynamic accuracy-configurable adders (DACAs) are further developed by cascading the PACAs or NACAs. The DACA design realizes a remarkable trade-off between accuracy and performance by switching between different degrees of approximations. Simulation results show that compared with an accurate adder, a 16-bit DACA provides a saving of up to 43.61% in power and a reduction of 83.31% in delay, with only a loss of 11.96% in accuracy. The advantage of the DACA is illustrated by applications of image processing and classification using a neural network model.

Near-threshold voltage (NTV) operation has the potential to improve the energy efficiency of digital integrated circuits. However, the use of a conservative timing guard band to avoid the timing errors introduces excessive timing margins, thus causing larger energy dissipation in the NTV region. An error-tolerant design based on timing error detection and correction circuits has been shown to be a promising solution to mitigate these issues. This paper presents a light-weight timing error-tolerant flip-flop (ETFF) design. This design detects timing errors using a node transition signal detector with only nine transistors and corrects these errors during the same clock cycle. Moreover, transistor sizing is explored to optimize the trade-off between performance and area overhead. The proposed ETFFs are inserted into a monitored circuit by replacing original flip-flops at timing-monitored points. To further reduce the overhead, we develop a mean-time-to-failure-aware method to select the monitored points by simultaneously considering the critical path coverage and activation rates of flip-flops. The simulation results show that a CNN accelerator using the proposed timing error-tolerant design implemented in the SMIC CMOS 40 nm process can robustly work at 1.1–0.3 V with only 3.5% area overhead. Furthermore, this design reduces the area overhead by 54.68% and improves the energy efficiency by 53.69% at 0.6 V, compared with the Razor flip-flop design. The advantage of the proposed design lies in that it requires smaller circuit overheads and can work reliably in a wider range of supply voltages.

Low-voltage computing effectively saves energy in circuit operations, but it suffers from an increasing propagation delay. Approximate computing can significantly reduce the propagation delay by using a simplified or improved circuit, albeit with an inevitable accuracy loss. To address these challenges, a timing-aware configurable adder (TACA) is proposed to achieve a good trade-off between energy efficiency and accuracy at low operating voltages. This design relies on the functions of timing-error detection and correction (TEDC) for the newly-proposed accuracy-configurable full adders (ACFAs). The ACFA operates in an exact mode and two approximate modes by using four transistors as power gates. The TEDC generates timing-error signals when the delay violates the timing constraint due to voltage overscaling. Then, an improved configuration scheme is developed to enable the ACFA to work in an approximate mode by allowing for error signals at runtime. This approximation shortens the carry propagation chain. Thus, the TACA is adapted to timing conditions at different supply voltages by reducing the propagation delay rather than the operation frequency.

Soft robotic systems have attracted increasing attention for hand rehabilitation because of their compliance, adaptability, and potential for comfortable human–robot interaction. However, the clinical translation of soft hand rehabilitation robots remains limited by insufficient integration of interactive training, user feedback, and practical wearability. This study presents a multimodal feedback-enhanced soft hand rehabilitation robot based on lattice-structured soft pneumatic actuators (LSPAs), together with a preliminary clinical evaluation. The system integrates a fabric-based soft glove, pneumatic actuation, fingertip force sensing, hand-motion tracking, and interactive virtual rehabilitation tasks to provide coordinated visual, auditory, force-related, and mirror-visual feedback. Material characterization was first conducted to compare three TPU materials with different mechanical properties, followed by system-level evaluation of usability, wearability, and actuator durability. A four-week robot-assisted rehabilitation intervention was then conducted in nine stroke survivors. Participants completed five one-hour sessions per week, including passive training and multimodal interactive training. Clinical outcomes were evaluated using the Brunnstrom motor recovery stage, Fugl–Meyer Assessment of the upper extremity (FMA-UE), National Institutes of Health Stroke Scale (NIHSS), and Activities of Daily Living (ADL) scale, while usability was assessed using the System Usability Scale (SUS). After four weeks, the mean Brunnstrom stage increased from $2.44\pm 2.07$ to $3.67\pm 2.12$, FMA-UE increased from $18.33\pm 25.63$ to $32.67\pm 23.11$, NIHSS decreased from $5.67\pm 4.36$ to $3.22\pm 2.99$, and ADL increased from $49.78\pm 39.53$ to $66.67\pm 22.50$. The mean SUS score was 74.4. TPU420D provided the best durability among the tested configurations, with more than 30 h of recorded use without failure during the experimental period. These findings support the feasibility and usability of the proposed system and provide preliminary evidence for its application in stroke hand rehabilitation. Because of the small sample size, heterogeneous post-stroke status, short intervention period, and absence of a control group, the clinical findings should be interpreted as preliminary rather than confirmatory evidence of therapeutic efficacy.