Pith. sign in

REVIEW 4 major objections 5 minor 37 references

picoRing: battery-free rings for subtle thumb-to-index input

T0 review · 4 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read A wristband-mounted reader coil can reliably read input from a battery-free ring weighing as little as 1.5 grams at a distance of 13 centimeters, using shifts in the ring's resonant frequency.

desk verdict Engineered readout is real; interaction claims outrun the evidence—send it to review with a request for per-input accuracy data. read the letter →

arxiv 2411.13065 v1 pith:GNLQXKS7 submitted 2024-11-20 cs.HC

Ryo Takahashi , Eric Whitmire , Roger Boldu , Shiu Ng , Wolf Kienzle , Hrvoje Benko This is my paper · ORCID
classification cs.HC
keywords coilwearablebattery-freeringwristbandsubtlefingerinputpassiveinductivetelemetryresonantfrequency
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

picoRing aims to show that a fully passive ring—one with no battery, no chip, and no transmitter—can work as a precise input device when paired with a wristband. The ring is a resonant coil loaded with a passive switch; pressing, sliding, or rotating the switch changes the ring's resonant frequency. The wristband contains a reader coil that picks up that frequency shift through weak inductive coupling, and the paper claims the readout is stable at up to 13 cm, across finger bending up to 70 degrees, and near running metal appliances. Four working rings, weighing 1.5 to 2.9 g, demonstrate press, slide, joystick, and scroll inputs. If this holds, smart rings no longer need batteries, and the wristband does all the power and computation.

What carries the argument

The central mechanism is passive inductive telemetry (PIT): a wristband reader coil excites a ring sensor coil and senses the reflected impedance $\Delta Z_{\mathrm{reader}}=(\omega M)^2/Z_{\mathrm{sensor}}$, which peaks sharply at the ring's resonant frequency $f_0=1/(2\pi\sqrt{L_{\mathrm{sensor}}C_{\mathrm{sensor}}})$. Because the coupling coefficient $k$ is below 0.002, the paper adds three techniques to make this tiny peak visible. Distributed capacitance arrangement (DCA) inserts chip capacitors in series along a long coil so it keeps high inductance at high frequency, and the paper raises the operating band to 27 MHz to gain about 10× sensitivity over earlier 13.5 MHz designs. A balanced bridge circuit matches the reader coil with a reference load so the output voltage is proportional only to the ring's impedance change, and a least-squares baseline fit removes slow amplitude and frequency drift before a peak detector recognizes the resonant-frequency shift. The ring side converts each input into a different resonant frequency using a mechanical switch that toggles a chip capacitor in or out of the sensor coil.

What would settle it

Recruit a diverse group of participants—spanning ring sizes and wrist shapes—and repeat the section 6.3 distance sweep and section 7.4 press-accuracy test with the same 5 cm wristband coil and 29 MHz ring; if a substantial share of typical hands falls below SNR 10 at 13 cm, or press accuracy drops noticeably from the reported 99.7%, the claimed stable readout does not generalize.

Watch

Extended reading notes

Core claim

On its own terms, the paper's discovery is that combining three sensitivity measures lets a compact wristband coil read a tiny passive ring coil that would otherwise produce an impedance change below 1 mΩ. Distributed capacitance arrangement keeps the coil inductance in the microhenry range at 27 MHz, the balanced bridge cancels the reader coil's own impedance so only the ring's contribution is measured, and a least-squares baseline-fit peak detector separates the ring's roughly 0.1 dB peak from slow drift caused by body capacitance and eddy currents. The paper reports SNR ≥ 10 at 13 cm (15 cm with no misalignment), insensitivity to finger bending up to 70 degrees, and robustness to six nearby metallic appliances. Four ring types—press, slide, joystick, scroll—encode inputs as distinct resonant frequencies, and a three-user test measured 99.7% press recognition at SNR 11–13.

Load-bearing premise

The load-bearing premise is that a hand-worn ring couples to the wristband coil through the simple series-resonant impedance model, with body and metal effects appearing only as a slowly varying baseline that the peak detector can remove, and that the mostly single-user SNR measurements transfer across hand sizes and wrist positions.

Editorial extensions

If this is right

  • Rings can be as light as 1.5 g and as thin as ordinary jewelry while supporting discrete and continuous thumb-to-index input, because power and processing move to the wristband.
  • The 13 cm readout distance—about 2.3 times the reader coil's diameter—means the reader can be a normal watch-sized wristband rather than a large cuff.
  • Since the ring is fully passive and chipless, its cost and failure modes are comparable to a simple coil and switch, which could make battery-free rings practical to deploy at scale.
  • The same reader architecture could be reused for other passive accessories, such as earbuds, gloves, or styluses, as the paper suggests in its conclusion.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A direct test of the generalization claim would be to repeat the SNR sweep and press-accuracy test across a wide range of hand sizes, since the prototype is sized for middle-sized hands and the main evaluation used users of similar hand size.
  • The turn-number optimum (SNR rises to 7–8 turns, then flattens) likely reflects a coil-loss trade-off that would reappear in other geometries; one could predict an optimal turn count from $R_{\mathrm{sensor}}$ and proximity-effect losses.
  • The baseline-fitting peak detector is a general tool: any weakly coupled passive sensor whose response drifts slowly could use the same trick, so the contribution may outlive this particular ring form factor.
  • The paper leaves implicit that assigning each interaction a distinct resonant frequency, rather than using four separate rings, would make a single ring support multiple inputs; the current prototype cannot do that because nearby rings with similar resonant frequencies interfere.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper presents picoRing, a coil-based sensing architecture in which a wristband reader coil inductively interrogates a fully passive ring coil. The ring contains passive switches that change its resonant frequency in response to press, slide, joystick, and scroll inputs. The authors claim that combining distributed-capacitance coils at 27 MHz, a balanced bridge circuit, and a baseline-fitting peak detector allows a 5 cm wristband coil to read a 1.5-2.9 g ring at up to 13 cm with SNR >= 10, and that this supports four types of thumb-to-index interaction. The manuscript reports SNR measurements as functions of turn count, frequency, distance, finger bending, and metal proximity, plus a press identification accuracy test with three participants.

Significance. If the claims are fully supported, picoRing would be a meaningful systems contribution to wearable input: it addresses a real usability barrier, namely battery bulk in smart rings, with a physically grounded and relatively simple sensing mechanism. The paper's strengths include the use of standard circuit theory for the core inductive link model, explicit baseline comparisons in §6.3, and candid acknowledgment of several limitations in §7.4 and §8. I found no circularity in the core derivations; the sensitivity figures are presented as empirical design results. However, the current empirical support is narrower than the stated contribution: the four-way interaction claim is validated only for binary press, and the technical evaluation is largely single-user. The core idea is credible, but the manuscript needs additional evidence or a scoped-down narrative before publication.

major comments (4)
  1. [§7.4 (also §7.2–§7.3)] The abstract and introduction claim that picoRing enables pressing, sliding, and scrolling, but the only input-recognition evaluation is for binary press. §7.4 reports 300 press trials across three users; §7.2 and §7.3 list the tuned frequencies for slide, joystick, and scroll states but provide no classification accuracy or confusion data for those states. This matters because the adjacent slide states are spaced by roughly 0.2–0.3 MHz (28.7, 28.4, 28.1, 27.9, 27.7, 27.6 MHz) while the VNA sweep step is 60 kHz, so the detector must separate peaks only a few bins apart, and the press accuracy already drops to 93.3% at SNR around 10. Please add state-level recognition results for slide, joystick, and scroll, or clearly revise the claims to specify that only the hardware for those inputs is demonstrated while interaction support remains to be evaluated. The manuscript's own sentence in §7.4 that a more through evaluation dedicated for each input through Fitts's law is necessary confirms this gap.
  2. [§6 (end) and §7.4] The technical evaluation that supports the headline 13 cm readout is almost entirely single-user. §6 states that the following evaluations were conducted for a single user after asserting minimal variation for similar hand sizes but without presenting supporting data. §7.4 uses three participants whose hand sizes were almost similar to fit the prototype, and §8 concedes the prototype is designed for middle-sized hands. No error bars or between-user SNR distributions are reported. Because a wristband/ring system is intended for varied users, these single-user measurements are load-bearing for the stable readout claim. Please report multi-user SNR measurements across a range of hand and wrist sizes, or explicitly scope the 13 cm claim to the tested geometry.
  3. [§6.2–§6.3 and §7.4] The paper treats SNR >= 10 as the criterion for a stable readout, but the only accuracy data show that press recognition at SNR around 10 is 93.3%, below the 99.7% achieved at SNR 11–13. If stable is meant to imply reliable input recognition, the threshold should be tied to a target accuracy; otherwise, the reader cannot tell whether the 13 cm headline distance corresponds to usable interaction or merely detectable peaks. Please state the accuracy target and report the readout distance at that target, or use a more conservative SNR threshold.
  4. [Abstract and §6.5] The abstract says picoRing achieves a 13 cm stable readout despite finger bending and proximity to metal, but §6.5 shows a clear exception: a metallic smart ring within 1 cm of the ring coil shifts the resonant frequency and disrupts the measurement. Since wearing a second ring on the same hand is a plausible real-world condition, the robustness claim should be qualified in the abstract and in §6.5 to state that the result holds for the tested metal appliances but not for a co-worn metallic ring near the sensor coil.
minor comments (5)
  1. [§7.4] The phrase a more through evaluation should be a more thorough evaluation.
  2. [§6.3] The statement that picoRing increases its SNR by approximately 13 compared to (i)(ii) should state whether 13 is a linear factor or a value in dB.
  3. [§3.3] The names scipy.polyfit and scipy.find_peaks are imprecise; the least-squares polynomial fit is typically numpy.polyfit, and a specific version or parameterization would improve reproducibility.
  4. [Table 2 and Figure 5] The SNR plots and the turn-number table would benefit from error bars or repeated-trial information to indicate measurement variability, especially because the technical evaluation is single-user.
  5. [Front matter] The manuscript uses the Conference'17 template with a 2018 copyright line and a placeholder DOI; these should be updated before submission.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the sensitivity, readout, and input claims rest on measured SNR data and standard circuit theory, with self-citations used only as comparative baselines.

full rationale

The paper's derivation chain is self-contained rather than circular. Section 3.2 Eqns. (1)-(5) are standard RLC circuit theory; the bridge equation follows algebraically from Z_ref = Z_reader and Z_reader >> Delta_Z_reader, and the reference load is then physically matched with chip elements (Section 5.1). DCA is justified by an external NMR reference [8], not by a self-citation. The claimed 'about 10x higher SNR' is an empirically measured comparison against the TelemetRing-style 13.5 MHz baseline in Section 6.3, not a constant retrofitted to match the paper's headline. The 13 cm readout distance is a direct measured SNR-vs-distance result (Figure 5b) using the system's own SNR >= 10 detection threshold; choosing the turn count from the measured SNR in Section 6.1 is ordinary design optimization, not a fitted parameter renamed as a prediction. Section 7.4 does concede that slide, joystick, and scroll lack dedicated Fitts's-law evaluation ('While a more through evaluation dedicated for each input through Fitts's law is necessary'), and Section 8 concedes the prototype is sized for middle-sized hands; these are empirical limitations, not circular dependencies. Citations [31]-[33] are prior work by the authors, but they are used as comparative baselines and implementation references, not as unverified premises that force the conclusion; the load-bearing evidence is the paper's own measurements. No equation in the paper is equivalent by construction to an input or fitted target, so no circular step is present.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The central 13 cm readout claim rests on standard coupled-circuit theory plus several empirically chosen engineering thresholds (peak threshold, SNR=10 cutoff, turn count). No novel physics or entities are introduced; the main assumptions are that switch states map cleanly to resonant frequencies and that interference acts as a removable baseline.

free parameters (3)
  • Peak detection threshold = 0.02 dB
    Chosen as 10x the VNA noise floor (0.002 dB) in §3.3; it determines whether a frequency peak is counted as input, so the 13 cm claim depends on it.
  • Minimum usable SNR threshold = 10 dB
    Used to define usable readout distance in §6.2-§6.3 and the accuracy test in §7.4; it is an operating threshold selected by the authors, not derived from first principles.
  • Ring coil turn count = 7 to 8
    Selected in §6.1 by measuring SNR for turn numbers 3 to 9; the choice maximizes SNR and is a fitted design parameter that affects ring size and readout distance.
assumptions (4)
  • standard math A ring coil and reader coil can be modeled as series RLC circuits whose mutual inductance obeys M = k sqrt(L1 L2).
    Used in §3.2 Eqs. (1)-(3) to derive the impedance change that the bridge detects; this is standard coupled-circuit theory.
  • standard math The resonant frequency of the ring follows f0 = 1/(2π√(L_sensor C_sensor)).
    States the canonical LC resonance formula in §3.1; the entire frequency-shift encoding relies on it.
  • domain assumption Body proximity, metal eddy currents, and EM noise can be treated as a slowly varying baseline that is removed by least-squares fitting in the peak detector.
    Invoked in §3.3 and §6.5 to argue robust detection; this is a working assumption about interference, not proven in general.
  • domain assumption Thumb-to-index gestures can be mapped one-to-one to states of passive mechanical switches (tactile, lever, joystick, reed).
    The four ring designs in §7 assume each switch state gives a distinct resonant frequency and that users perform the intended gesture; inter-user variability beyond hand size is not modeled.

how reviews work

0 comments
Cite this review

Pith. "Pith review of picoRing: battery-free rings for subtle thumb-to-index input." pith.science (2026). https://pith.science/paper/GNLQXKS7

@misc{pith2026241113065,
  author       = {Pith},
  title        = {Pith review of: picoRing: battery-free rings for subtle thumb-to-index input},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GNLQXKS7}},
  note         = {Machine review of arXiv:2411.13065}
}
read the original abstract

Smart rings for subtle, reliable finger input offer an attractive path for ubiquitous interaction with wearable computing platforms. However, compared to ordinary rings worn for cultural or fashion reasons, smart rings are much bulkier and less comfortable, largely due to the space required for a battery, which also limits the space available for sensors. This paper presents picoRing, a flexible sensing architecture that enables a variety of \textit{battery-free} smart rings paired with a wristband. By inductively connecting a wristband-based sensitive reader coil with a ring-based fully-passive sensor coil, picoRing enables the wristband to stably detect the passive response from the ring via a weak inductive coupling. We demonstrate four different rings that support thumb-to-finger interactions like pressing, sliding, or scrolling. When users perform these interactions, the corresponding ring converts each input into a unique passive response through a network of passive switches. Combining the coil-based sensitive readout with the fully-passive ring design enables a tiny ring that weighs as little as 1.5 g and achieves a 13 cm stable readout despite finger bending, and proximity to metal.

Figures

Figures reproduced from arXiv: 2411.13065 by the authors.

Figure 1
Figure 1. Overview of picoRing. picoRing is a flexible sensing architecture enabling a variety of [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. picoRing design. (a) The system illustration of picoRing. picoRing is based on passive inductive telemetry (PIT), in [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Design of passive variable capacitor. Among three types, picoRing uses type 1. [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: Implementation of a wristband coil [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]
Figure 5
Figure 5. Figure 5: SNR evaluation of picoRing. (a) SNR for the resonant frequency of the ring coil. (b) SNR for the distance between the [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: picoRing demonstration. Photograph, application example, and peak in the frequency response of picoRing (a) [PITH_FULL_IMAGE:figures/full_fig_p009_6.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

37 extracted references · 12 canonical work pages

  1. [1]

    Daniel Ashbrook, Patrick Baudisch, and Sean White. 2011. Nenya: Subtle and Eyes-Free Mobile Input with a Magnetically-Tracked Finger Ring. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, BC, Canada) (CHI ’11). New York, NY, USA, 2043–2046. https://doi.org/10.1145/ 1978942.1979238

    arXiv 2011

  2. [2]

    Scott MacKenzie

    Ravin Balakrishnan and I. Scott MacKenzie. 1997. Performance Differences in the Fingers, Wrist, and Forearm in Computer Input Control. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (Atlanta, Georgia, USA) (CHI ’97). Association for Computing Machinery, New York, NY, USA, 303–310. https://doi.org/10.1145/258549.258764

    arXiv 1997

  3. [3]

    Matthies, Thisum Buddhika, Shamane Siriwardhana, and Suranga Nanayakkara

    Roger Boldu, Alexandru Dancu, Denys J.C. Matthies, Thisum Buddhika, Shamane Siriwardhana, and Suranga Nanayakkara. 2018. FingerReader2.0: Designing and Evaluating a Wearable Finger-Worn Camera to Assist People with Visual Impairments While Shopping. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 3, Article 94 (sep 2018), 19 pages. https://doi.or...

    work page doi:10.1145/3264904 2018

  4. [4]

    Edwin Chan, Teddy Seyed, Wolfgang Stuerzlinger, Xing-Dong Yang, and Frank Maurer. 2016. User Elicitation on Single-Hand Microgestures. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 3403–3414. https://doi.org/10.1145/2858036.2858589

    arXiv 2016

  5. [5]

    Chen, Wen-Huang Cheng, and Bing-Yu Chen

    Liwei Chan, Rong-Hao Liang, Ming-Chang Tsai, Kai-Yin Cheng, Chao-Huai Su, Mike Y. Chen, Wen-Huang Cheng, and Bing-Yu Chen. 2013. FingerPad: Private and Subtle Interaction Using Fingertips. In Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology (St. Andrews, Scotland, United Kingdom) (UIST ’13). Association for Computing ...

    arXiv 2013

  6. [6]

    Patel, and Sean Keller

    Ke-Yu Chen, Shwetak N. Patel, and Sean Keller. 2016. Finexus: Tracking Precise Motions of Multiple Fingertips Using Magnetic Sensing. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems . New York, NY, USA, 1504–1514. https://doi.org/10.1145/2858036.2858125

    arXiv 2016

  7. [7]

    Taizhou Chen, Tianpei Li, Xingyu Yang, and Kening Zhu. 2023. EFRing: Enabling Thumb-to-Index-Finger Microgesture Interaction through Electric Field Sensing Using Single Smart Ring. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 4, Article 161 (jan 2023), 31 pages. https://doi.org/10.1145/3569478

    work page doi:10.1145/3569478 2023

  8. [8]

    Bruce Cook and I.J Lowe. 1982. A large-inductance, high-frequency, high-Q, series-tuned coil for NMR. Journal of Magnetic Resonance (1969) 49, 2 (9 1982), 346–349. https://doi.org/10.1016/0022-2364(82)90200-1

    work page doi:10.1016/0022-2364(82)90200-1 1969

Show all 37 references
  1. [10]

    Masaaki Fukumoto and Yoshinobu Tonomura. 1997. ”Body coupled FingerRing": Wireless Wearable Keyboard. In Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’97 . New York, NY, USA, 147–154. https: //doi.org/10.1145/258549.258636 picoRing Conferenc...

    1997

  2. [11]

    Jun Gong, Yang Zhang, Xia Zhou, and Xing-Dong Yang. 2017. Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing. In Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology - UIST ’17. New York, NY, USA, 553–563. https://doi.org/...

    2017

  3. [12]

    Tovi Grossman, Xiang Anthony Chen, and George Fitzmaurice. 2015. Typing on Glasses: Adapting Text Entry to Smart Eyewear. InProceedings of the 17th Interna- tional Conference on Human-Computer Interaction with Mobile Devices and Services (Copenhagen, Denmark) (MobileHCI ’15). ...

    2015

  4. [14]

    Aakar Gupta, Cheng Ji, Hui-Shyong Yeo, Aaron Quigley, and Daniel Vogel. 2019. RotoSwype: Word-Gesture Typing Using a Ring. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19) . Association for Computing Machinery, Ne...

    2019

  5. [15]

    Jiawei Huang, Ryo Sugawara, Kinfung Chu, Taku Komura, and Yoshifumi Ki- tamura. 2022. Reconstruction of Dexterous 3D Motion Data From a Flexible Magnetic Sensor With Deep Learning and Structure-Aware Filtering. IEEE Transactions on Visualization and Computer Graphics 28, 6 (20...

    2022

  6. [16]

    Lo, and Peter B

    Shuo Jiang, Peiqi Kang, Xinyu Song, Benny P.L. Lo, and Peter B. Shull. 2022. Emerging Wearable Interfaces and Algorithms for Hand Gesture Recognition: A Survey. IEEE Reviews in Biomedical Engineering 15 (2022), 85–102. https: //doi.org/10.1109/RBME.2021.3078190

    2022

  7. [17]

    Wolf Kienzle and Ken Hinckley. 2014. LightRing: Always-Available 2D Input on Any Surface. In Proceedings of the 27th Annual ACM Symposium on User Interface Software and Technology (Honolulu, Hawaii, USA) (UIST ’14). New York, NY, USA, 157–160. https://doi.org/10.1145/2642918.2647376

    2014

  8. [18]

    Wolf Kienzle, Eric Whitmire, Chris Rittaler, and Hrvoje Benko. 2021. ElectroRing: Subtle Pinch and Touch Detection with a Ring (CHI ’21). New York, NY, USA, Article 3, 12 pages. https://doi.org/10.1145/3411764.3445094

    2021

  9. [19]

    Daehwa Kim and Chris Harrison. 2022. EtherPose: Continuous Hand Pose Tracking with Wrist-Worn Antenna Impedance Characteristic Sensing. InPro- ceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (Bend, OR, USA) (UIST ’22). New York, NY, USA, Art...

    2022

  10. [21]

    Chen Liang, Chun Yu, Yue Qin, Yuntao Wang, and Yuanchun Shi. 2021. DualRing: Enabling Subtle and Expressive Hand Interaction with Dual IMU Rings. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 3, Article 115 (sep 2021), 27 pages. https://doi.org/10.1145/3478114

    2021 doi

  11. [22]

    Kurt, Shawn C

    Rongzhou Lin, Han-Joon Kim, Sippanat Achavananthadith, Selman A. Kurt, Shawn C. C. Tan, Haicheng Yao, Benjamin C. K. Tee, Jason K. W. Lee, and John S. Ho. 2020. Wireless battery-free body sensor networks using near-field-enabled clothing. Nature Communications 11, 1 (2020), 44...

    2020

  12. [23]

    Meskers, H.M

    C.G.M. Meskers, H.M. Vermeulen, J.H. de Groot, F.C.T. van der Helm, and P.M. Rozing. 1998. 3D shoulder position measurements using a six-degree-of-freedom electromagnetic tracking device. Clinical Biomechanics 13, 4 (1998), 280–292. https://doi.org/10.1016/S0268-0033(98)00095-3

    1998 doi

  13. [24]

    Saman Naderiparizi, Mehrdad Hessar, Vamsi Talla, Shyamnath Gollakota, and Joshua R Smith. 2018. Towards Battery-Free HD Video Streaming. In15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18) . USENIX Association, Renton, WA, 233–247

    2018

  14. [25]

    Shahriar Nirjon, Jeremy Gummeson, Dan Gelb, and Kyu-Han Kim. 2015. Typ- ingRing: A Wearable Ring Platform for Text Input. In Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services (Florence, Italy) (MobiSys ’15). New York, NY, USA...

    2015

  15. [26]

    Farshid Salemi Parizi, Eric Whitmire, and Shwetak Patel. 2019. AuraRing: Precise Electromagnetic Finger Tracking. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 4 (12 2019), 1–28. https://doi.org/10. 1145/3369831

    2019

  16. [27]

    Raab, Ernest B

    Frederick H. Raab, Ernest B. Blood, Terry O. Steiner, and Herbert R. Jones. 1979. Magnetic Position and Orientation Tracking System. IEEE Trans. Aerospace Electron. Systems AES-15, 5 (1979), 709–718. https://doi.org/10.1109/TAES.1979. 308860

    1979 doi

  17. [28]

    Jun Rekimoto. 2001. GestureWrist and GesturePad: unobtrusive wearable interac- tion devices. In Proceedings Fifth International Symposium on Wearable Computers. 21–27

    2001

  18. [29]

    Keith Edwards, Gregory D

    Gabriel Reyes, Jason Wu, Nikita Juneja, Maxim Goldshtein, W. Keith Edwards, Gregory D. Abowd, and Thad Starner. 2018. SynchroWatch: One-Handed Syn- chronous Smartwatch Gestures Using Correlation and Magnetic Sensing. 1, 4, Article 158 (jan 2018), 26 pages. https://doi.org/10.1...

    2018 doi

  19. [30]

    Scott Saponas, Desney S

    T. Scott Saponas, Desney S. Tan, Dan Morris, Ravin Balakrishnan, Jim Turner, and James A. Landay. 2009. Enabling Always-Available Input with Muscle- Computer Interfaces. In Proceedings of the 22nd Annual ACM Symposium on User Interface Software and Technology (Victoria, BC, Ca...

    2009

  20. [32]

    Ryo Takahashi, Wakako Yukita, Takuya Sasatani, Tomoyuki Yokota, Takao Someya, and Yoshihiro Kawahara. 2022. Twin Meander Coil: Sensitive Readout of Battery-Free On-Body Wireless Sensors Using Body-Scale Meander Coils. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 4,...

    2022 doi

  21. [33]

    Ryo Takahashi, Wakako Yukita, Tomoyuki Yokota, Takao Someya, and Yoshihiro Kawahara. 2022. Meander Coil++: A Body-Scale Wireless Power Transmission Using Safe-to-Body and Energy-Efficient Transmitter Coil. In Proceedings of the 2022 CHI Conference on Human Factors in Computing...

    2022

  22. [34]

    Andrew Vardy, John Robinson, and Li-Te Cheng. 1999. The WristCam as input device. In Digest of Papers. Third International Symposium on Wearable Computers. 199–202. https://doi.org/10.1109/ISWC.1999.806928

    1999

  23. [35]

    Radu-Daniel Vatavu. 2023. IFAD Gestures: Understanding Users’ Gesture Input Performance with Index-Finger Augmentation Devices. InProceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23). Association for Computing Machinery, New...

    2023

  24. [36]

    Anandghan Waghmare, Roger Boldu, Eric Whitmire, and Wolf Kienzle. 2023. OptiRing: Low-Resolution Optical Sensing for Subtle Thumb-to-Index Micro- Interactions. In Proceedings of the 2023 ACM Symposium on Spatial User Interaction (Sydney, NSW, Australia)(SUI ’23). Association f...

    2023

  25. [37]

    Erwin Wu, Ye Yuan, Hui-Shyong Yeo, Aaron Quigley, Hideki Koike, and Kris M. Kitani. 2020. Back-Hand-Pose: 3D Hand Pose Estimation for a Wrist-Worn Camera via Dorsum Deformation Network. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (...

    2020

  26. [38]

    Chenhan Xu, Bing Zhou, Gurunandan Krishnan, and Shree Nayar. 2023. AO- Finger: Hands-Free Fine-Grained Finger Gesture Recognition via Acoustic-Optic Sensor Fusing. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23). Ass...

    2023

  27. [39]

    Xuhai Xu, Jun Gong, Carolina Brum, Lilian Liang, Bongsoo Suh, Shivam Kumar Gupta, Yash Agarwal, Laurence Lindsey, Runchang Kang, Behrooz Shahsavari, Tu Nguyen, Heriberto Nieto, Scott E Hudson, Charlie Maalouf, Jax Seyed Mousavi, and Gierad Laput. 2022. Enabling Hand Gesture Cu...

    2022

  28. [40]

    Shumin Zhai, Paul Milgram, and William Buxton. 1996. The Influence of Muscle Groups on Performance of Multiple Degree-of-Freedom Input. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, British Columbia, Canada) (CHI ’96). Association fo...

    1996

  29. [41]

    Yang Zhang, Robert Xiao, and Chris Harrison. 2016. Advancing Hand Gesture Recognition with High Resolution Electrical Impedance Tomography. In Proceed- ings of the 29th Annual Symposium on User Interface Software and Technology (Tokyo, Japan) (UIST ’16). Association for Comput...

    2016

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.